Overview

Dataset statistics

Number of variables39
Number of observations1880465
Missing cells19788951
Missing cells (%)27.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 GiB
Average record size in memory1.5 KiB

Variable types

CAT27
NUM12

Warnings

FPA_ID has a high cardinality: 1880462 distinct values High cardinality
NWCG_REPORTING_UNIT_ID has a high cardinality: 1640 distinct values High cardinality
NWCG_REPORTING_UNIT_NAME has a high cardinality: 1635 distinct values High cardinality
SOURCE_REPORTING_UNIT has a high cardinality: 4992 distinct values High cardinality
SOURCE_REPORTING_UNIT_NAME has a high cardinality: 4441 distinct values High cardinality
LOCAL_FIRE_REPORT_ID has a high cardinality: 13508 distinct values High cardinality
LOCAL_INCIDENT_ID has a high cardinality: 565914 distinct values High cardinality
FIRE_CODE has a high cardinality: 172446 distinct values High cardinality
FIRE_NAME has a high cardinality: 493633 distinct values High cardinality
ICS_209_INCIDENT_NUMBER has a high cardinality: 22737 distinct values High cardinality
ICS_209_NAME has a high cardinality: 19573 distinct values High cardinality
MTBS_ID has a high cardinality: 10481 distinct values High cardinality
MTBS_FIRE_NAME has a high cardinality: 8133 distinct values High cardinality
COMPLEX_NAME has a high cardinality: 1416 distinct values High cardinality
DISCOVERY_TIME has a high cardinality: 1440 distinct values High cardinality
CONT_TIME has a high cardinality: 1441 distinct values High cardinality
STATE has a high cardinality: 52 distinct values High cardinality
COUNTY has a high cardinality: 3455 distinct values High cardinality
FIPS_CODE has a high cardinality: 285 distinct values High cardinality
FIPS_NAME has a high cardinality: 1698 distinct values High cardinality
Shape has a high cardinality: 1569708 distinct values High cardinality
DISCOVERY_DATE is highly correlated with FIRE_YEAR and 1 other fieldsHigh correlation
FIRE_YEAR is highly correlated with DISCOVERY_DATE and 1 other fieldsHigh correlation
CONT_DATE is highly correlated with FIRE_YEAR and 1 other fieldsHigh correlation
CONT_DOY is highly correlated with DISCOVERY_DOYHigh correlation
DISCOVERY_DOY is highly correlated with CONT_DOYHigh correlation
SOURCE_SYSTEM is highly correlated with SOURCE_SYSTEM_TYPEHigh correlation
SOURCE_SYSTEM_TYPE is highly correlated with SOURCE_SYSTEMHigh correlation
LOCAL_FIRE_REPORT_ID has 1459286 (77.6%) missing values Missing
LOCAL_INCIDENT_ID has 820821 (43.6%) missing values Missing
FIRE_CODE has 1555636 (82.7%) missing values Missing
FIRE_NAME has 957189 (50.9%) missing values Missing
ICS_209_INCIDENT_NUMBER has 1854748 (98.6%) missing values Missing
ICS_209_NAME has 1854748 (98.6%) missing values Missing
MTBS_ID has 1869462 (99.4%) missing values Missing
MTBS_FIRE_NAME has 1869462 (99.4%) missing values Missing
COMPLEX_NAME has 1875282 (99.7%) missing values Missing
DISCOVERY_TIME has 882638 (46.9%) missing values Missing
CONT_DATE has 891531 (47.4%) missing values Missing
CONT_DOY has 891531 (47.4%) missing values Missing
CONT_TIME has 972173 (51.7%) missing values Missing
COUNTY has 678148 (36.1%) missing values Missing
FIPS_CODE has 678148 (36.1%) missing values Missing
FIPS_NAME has 678148 (36.1%) missing values Missing
FIRE_SIZE is highly skewed (γ1 = 106.83733) Skewed
FPA_ID is uniformly distributed Uniform
MTBS_ID is uniformly distributed Uniform
OBJECTID has unique values Unique
FOD_ID has unique values Unique

Reproduction

Analysis started2020-11-18 23:56:01.915679
Analysis finished2020-11-19 00:03:56.160728
Duration7 minutes and 54.25 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

OBJECTID
Real number (ℝ≥0)

UNIQUE

Distinct1880465
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean940233
Minimum1
Maximum1880465
Zeros0
Zeros (%)0.0%
Memory size14.3 MiB
2020-11-18T18:03:57.269440image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile94024.2
Q1470117
median940233
Q31410349
95-th percentile1786441.8
Maximum1880465
Range1880464
Interquartile range (IQR)940232

Descriptive statistics

Standard deviation542843.6313
Coefficient of variation (CV)0.5773501157
Kurtosis-1.2
Mean940233
Median Absolute Deviation (MAD)470116
Skewness1.089334184e-15
Sum1.768075248e+12
Variance2.946792081e+11
MonotocityStrictly increasing
2020-11-18T18:03:57.458452image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
20471< 0.1%
 
8670851< 0.1%
 
8629911< 0.1%
 
9060001< 0.1%
 
9080491< 0.1%
 
9019061< 0.1%
 
9039551< 0.1%
 
9141961< 0.1%
 
9162451< 0.1%
 
9101021< 0.1%
 
9121511< 0.1%
 
8896241< 0.1%
 
8916731< 0.1%
 
8855301< 0.1%
 
8875791< 0.1%
 
8978201< 0.1%
 
8998691< 0.1%
 
8937261< 0.1%
 
8957751< 0.1%
 
8077121< 0.1%
 
8097611< 0.1%
 
8036181< 0.1%
 
8056671< 0.1%
 
8159081< 0.1%
 
8179571< 0.1%
 
Other values (1880440)1880440> 99.9%
 
ValueCountFrequency (%) 
11< 0.1%
 
21< 0.1%
 
31< 0.1%
 
41< 0.1%
 
51< 0.1%
 
61< 0.1%
 
71< 0.1%
 
81< 0.1%
 
91< 0.1%
 
101< 0.1%
 
ValueCountFrequency (%) 
18804651< 0.1%
 
18804641< 0.1%
 
18804631< 0.1%
 
18804621< 0.1%
 
18804611< 0.1%
 
18804601< 0.1%
 
18804591< 0.1%
 
18804581< 0.1%
 
18804571< 0.1%
 
18804561< 0.1%
 

FOD_ID
Real number (ℝ≥0)

UNIQUE

Distinct1880465
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54840199.02
Minimum1
Maximum300348399
Zeros0
Zeros (%)0.0%
Memory size14.3 MiB
2020-11-18T18:03:58.670699image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile95062.2
Q1505500
median1067761
Q319106386
95-th percentile300146219.8
Maximum300348399
Range300348398
Interquartile range (IQR)18600886

Descriptive statistics

Standard deviation101196328.6
Coefficient of variation (CV)1.8452947
Kurtosis0.5848193526
Mean54840199.02
Median Absolute Deviation (MAD)700448
Skewness1.511181964
Sum1.031250749e+14
Variance1.024069692e+16
MonotocityNot monotonic
2020-11-18T18:03:58.852513image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
20471< 0.1%
 
2055191< 0.1%
 
2505771< 0.1%
 
2485301< 0.1%
 
2464831< 0.1%
 
2608201< 0.1%
 
2587731< 0.1%
 
2567261< 0.1%
 
2546791< 0.1%
 
2362481< 0.1%
 
2342011< 0.1%
 
2321541< 0.1%
 
2444441< 0.1%
 
2423971< 0.1%
 
2403501< 0.1%
 
2383031< 0.1%
 
1543361< 0.1%
 
1522891< 0.1%
 
1502421< 0.1%
 
1481951< 0.1%
 
1625321< 0.1%
 
1604851< 0.1%
 
1584381< 0.1%
 
1563911< 0.1%
 
1379601< 0.1%
 
Other values (1880440)1880440> 99.9%
 
ValueCountFrequency (%) 
11< 0.1%
 
21< 0.1%
 
31< 0.1%
 
41< 0.1%
 
51< 0.1%
 
61< 0.1%
 
71< 0.1%
 
81< 0.1%
 
91< 0.1%
 
101< 0.1%
 
ValueCountFrequency (%) 
3003483991< 0.1%
 
3003483771< 0.1%
 
3003483751< 0.1%
 
3003483731< 0.1%
 
3003483631< 0.1%
 
3003483621< 0.1%
 
3003483611< 0.1%
 
3003483541< 0.1%
 
3003483281< 0.1%
 
3003483111< 0.1%
 

FPA_ID
Categorical

HIGH CARDINALITY
UNIFORM

Distinct1880462
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size14.3 MiB
SFO-2015CACDFLNU003791
 
2
ICS209_2009_KS-DDQ-128
 
2
FS-1452833
 
2
TFS_NC_221295
 
1
CDF_2005_54_2218_009308
 
1
Other values (1880457)
1880457 
ValueCountFrequency (%) 
SFO-2015CACDFLNU0037912< 0.1%
 
ICS209_2009_KS-DDQ-1282< 0.1%
 
FS-14528332< 0.1%
 
TFS_NC_2212951< 0.1%
 
CDF_2005_54_2218_009308 1< 0.1%
 
SFO-MN0349-9224551< 0.1%
 
2011CACDFMMU0167851< 0.1%
 
W-6810361< 0.1%
 
TFS_FL_471261< 0.1%
 
SFO-LA00690505-14141< 0.1%
 
FS-3373331< 0.1%
 
SFO-2013119450000591< 0.1%
 
NM97-51720443X1< 0.1%
 
SFO-TN-2007-1931< 0.1%
 
CDF_2001_56_2229_003418 1< 0.1%
 
SC_140061< 0.1%
 
SFO-TN-2012-105991< 0.1%
 
FS-3230381< 0.1%
 
SWRA_TN_134331< 0.1%
 
TFS-TXFD2010-2369451< 0.1%
 
FS-3215131< 0.1%
 
W-5018661< 0.1%
 
SFO-NY-NY3036-2000-00005581< 0.1%
 
SFO-NY-NY1560-2006-060221< 0.1%
 
TFS_FL_852161< 0.1%
 
Other values (1880437)1880437> 99.9%
 
2020-11-18T18:04:11.399880image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1880459 ?
Unique (%)> 99.9%
2020-11-18T18:04:11.535881image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length49
Median length16
Mean length16.53853382
Min length3

Overview of Unicode Properties

Unique unicode characters73
Unique unicode categories11 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
0377013212.1%
 
-29179549.4%
 
124628797.9%
 
223845567.7%
 
S17151525.5%
 
F15755665.1%
 
314503124.7%
 
513941704.5%
 
413885144.5%
 
912146033.9%
 
611369223.7%
 
_9780723.1%
 
79279503.0%
 
88866972.9%
 
O8235392.6%
 
A7221432.3%
 
5730611.8%
 
T5469571.8%
 
C5047291.6%
 
W4876921.6%
 
N4511281.5%
 
D2933240.9%
 
R2684410.9%
 
M2582290.8%
 
Y2496490.8%
 
Other values (48)17177635.5%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number1701673554.7%
 
Uppercase Letter918399729.5%
 
Dash Punctuation29179549.4%
 
Connector Punctuation9780723.1%
 
Space Separator5730611.8%
 
Lowercase Letter3107981.0%
 
Other Punctuation1098070.4%
 
Open Punctuation4853< 0.1%
 
Close Punctuation4853< 0.1%
 
Math Symbol3< 0.1%
 
Modifier Symbol1< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
S171515218.7%
 
F157556617.2%
 
O8235399.0%
 
A7221437.9%
 
T5469576.0%
 
C5047295.5%
 
W4876925.3%
 
N4511284.9%
 
D2933243.2%
 
R2684412.9%
 
M2582292.8%
 
Y2496492.7%
 
L2357942.6%
 
G2046652.2%
 
I1821762.0%
 
X1677621.8%
 
H978311.1%
 
E887531.0%
 
K765390.8%
 
V573120.6%
 
U473310.5%
 
B401390.4%
 
J337930.4%
 
P307010.3%
 
Z233370.3%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-2917954100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
0377013222.2%
 
1246287914.5%
 
2238455614.0%
 
314503128.5%
 
513941708.2%
 
413885148.2%
 
912146037.1%
 
611369226.7%
 
79279505.5%
 
88866975.2%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_978072100.0%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
573061100.0%
 

Most frequent Modifier Symbol characters

ValueCountFrequency (%) 
`1100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
e3492411.2%
 
n304409.8%
 
o296859.6%
 
a289999.3%
 
r276568.9%
 
l235847.6%
 
i184265.9%
 
t169745.5%
 
s144934.7%
 
h107263.5%
 
u105583.4%
 
c84992.7%
 
f76602.5%
 
k76052.4%
 
d69142.2%
 
g68462.2%
 
y65622.1%
 
m62082.0%
 
w45781.5%
 
p42521.4%
 
b27450.9%
 
v14560.5%
 
q5570.2%
 
x4510.1%
 

Most frequent Math Symbol characters

ValueCountFrequency (%) 
=266.7%
 
+133.3%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/10771998.1%
 
.10631.0%
 
,10230.9%
 
*1< 0.1%
 
#1< 0.1%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(4853100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)4853100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common2160533969.5%
 
Latin949479530.5%
 

Most frequent Latin characters

ValueCountFrequency (%) 
S171515218.1%
 
F157556616.6%
 
O8235398.7%
 
A7221437.6%
 
T5469575.8%
 
C5047295.3%
 
W4876925.1%
 
N4511284.8%
 
D2933243.1%
 
R2684412.8%
 
M2582292.7%
 
Y2496492.6%
 
L2357942.5%
 
G2046652.2%
 
I1821761.9%
 
X1677621.8%
 
H978311.0%
 
E887530.9%
 
K765390.8%
 
V573120.6%
 
U473310.5%
 
B401390.4%
 
e349240.4%
 
J337930.4%
 
P307010.3%
 
Other values (25)3005263.2%
 

Most frequent Common characters

ValueCountFrequency (%) 
0377013217.5%
 
-291795413.5%
 
1246287911.4%
 
2238455611.0%
 
314503126.7%
 
513941706.5%
 
413885146.4%
 
912146035.6%
 
611369225.3%
 
_9780724.5%
 
79279504.3%
 
88866974.1%
 
5730612.7%
 
/1077190.5%
 
(4853< 0.1%
 
)4853< 0.1%
 
.1063< 0.1%
 
,1023< 0.1%
 
=2< 0.1%
 
`1< 0.1%
 
*1< 0.1%
 
#1< 0.1%
 
+1< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII31100134100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
0377013212.1%
 
-29179549.4%
 
124628797.9%
 
223845567.7%
 
S17151525.5%
 
F15755665.1%
 
314503124.7%
 
513941704.5%
 
413885144.5%
 
912146033.9%
 
611369223.7%
 
_9780723.1%
 
79279503.0%
 
88866972.9%
 
O8235392.6%
 
A7221432.3%
 
5730611.8%
 
T5469571.8%
 
C5047291.6%
 
W4876921.6%
 
N4511281.5%
 
D2933240.9%
 
R2684410.9%
 
M2582290.8%
 
Y2496490.8%
 
Other values (48)17177635.5%
 

SOURCE_SYSTEM_TYPE
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size14.3 MiB
NONFED
1362148 
FED
481106 
INTERAGCY
 
37211
ValueCountFrequency (%) 
NONFED136214872.4%
 
FED48110625.6%
 
INTERAGCY372112.0%
 
2020-11-18T18:04:11.653881image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-18T18:04:11.721876image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:04:11.801883image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length9
Median length6
Mean length5.291832073
Min length3

Overview of Unicode Properties

Unique unicode characters12
Unique unicode categories1 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
N276150727.8%
 
E188046518.9%
 
F184325418.5%
 
D184325418.5%
 
O136214813.7%
 
I372110.4%
 
T372110.4%
 
R372110.4%
 
A372110.4%
 
G372110.4%
 
C372110.4%
 
Y372110.4%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter9951105100.0%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
N276150727.8%
 
E188046518.9%
 
F184325418.5%
 
D184325418.5%
 
O136214813.7%
 
I372110.4%
 
T372110.4%
 
R372110.4%
 
A372110.4%
 
G372110.4%
 
C372110.4%
 
Y372110.4%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin9951105100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
N276150727.8%
 
E188046518.9%
 
F184325418.5%
 
D184325418.5%
 
O136214813.7%
 
I372110.4%
 
T372110.4%
 
R372110.4%
 
A372110.4%
 
G372110.4%
 
C372110.4%
 
Y372110.4%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII9951105100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
N276150727.8%
 
E188046518.9%
 
F184325418.5%
 
D184325418.5%
 
O136214813.7%
 
I372110.4%
 
T372110.4%
 
R372110.4%
 
A372110.4%
 
G372110.4%
 
C372110.4%
 
Y372110.4%
 

SOURCE_SYSTEM
Categorical

HIGH CORRELATION

Distinct38
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size14.3 MiB
ST-NASF
711236 
DOI-WFMI
241423 
FS-FIRESTAT
220356 
ST-CACDF
87355 
ST-NCNCS
 
65695
Other values (33)
554400 
ValueCountFrequency (%) 
ST-NASF71123637.8%
 
DOI-WFMI24142312.8%
 
FS-FIRESTAT22035611.7%
 
ST-CACDF873554.6%
 
ST-NCNCS656953.5%
 
ST-GAGAS650613.5%
 
ST-MSMSS605133.2%
 
ST-TXTXS579453.1%
 
ST-ALALS549512.9%
 
ST-SCSCS492812.6%
 
ST-FLFLS450772.4%
 
IA-PRIITF218021.2%
 
FWS-FMIS193271.0%
 
ST-ORORS181211.0%
 
ST-LALAS161720.9%
 
ST-OKOKS153970.8%
 
ST-TNTNS147770.8%
 
ST-WIWIS143230.8%
 
ST-ARARS113030.6%
 
ST-VAVAS105750.6%
 
ST-MOMOS98350.5%
 
IA-HIWMO97140.5%
 
ST-WAWAS96480.5%
 
ST-MEMES72520.4%
 
ST-KYKYS65190.3%
 
Other values (13)368072.0%
 
2020-11-18T18:04:12.084874image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-18T18:04:12.200874image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length11
Median length8
Mean length7.98596996
Min length7

Overview of Unicode Properties

Unique unicode characters27
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
S334085122.2%
 
T198789013.2%
 
-188046512.5%
 
F163811010.9%
 
A14092849.4%
 
N8844675.9%
 
I8513535.7%
 
M4442823.0%
 
C4256952.8%
 
O3427092.3%
 
D3351402.2%
 
W3213842.1%
 
R3043932.0%
 
E2348941.6%
 
L2324001.5%
 
G1301220.9%
 
X1158900.8%
 
K475450.3%
 
P218020.1%
 
V211500.1%
 
Y160160.1%
 
H97140.1%
 
U89400.1%
 
Z6892< 0.1%
 
21983< 0.1%
 
Other values (2)3966< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter1313092387.4%
 
Dash Punctuation188046512.5%
 
Decimal Number5949< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
S334085125.4%
 
T198789015.1%
 
F163811012.5%
 
A140928410.7%
 
N8844676.7%
 
I8513536.5%
 
M4442823.4%
 
C4256953.2%
 
O3427092.6%
 
D3351402.6%
 
W3213842.4%
 
R3043932.3%
 
E2348941.8%
 
L2324001.8%
 
G1301221.0%
 
X1158900.9%
 
K475450.4%
 
P218020.2%
 
V211500.2%
 
Y160160.1%
 
H97140.1%
 
U89400.1%
 
Z68920.1%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-1880465100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
2198333.3%
 
0198333.3%
 
9198333.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin1313092387.4%
 
Common188641412.6%
 

Most frequent Latin characters

ValueCountFrequency (%) 
S334085125.4%
 
T198789015.1%
 
F163811012.5%
 
A140928410.7%
 
N8844676.7%
 
I8513536.5%
 
M4442823.4%
 
C4256953.2%
 
O3427092.6%
 
D3351402.6%
 
W3213842.4%
 
R3043932.3%
 
E2348941.8%
 
L2324001.8%
 
G1301221.0%
 
X1158900.9%
 
K475450.4%
 
P218020.2%
 
V211500.2%
 
Y160160.1%
 
H97140.1%
 
U89400.1%
 
Z68920.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
-188046599.7%
 
219830.1%
 
019830.1%
 
919830.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII15017337100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
S334085122.2%
 
T198789013.2%
 
-188046512.5%
 
F163811010.9%
 
A14092849.4%
 
N8844675.9%
 
I8513535.7%
 
M4442823.0%
 
C4256952.8%
 
O3427092.3%
 
D3351402.2%
 
W3213842.1%
 
R3043932.0%
 
E2348941.6%
 
L2324001.5%
 
G1301220.9%
 
X1158900.8%
 
K475450.3%
 
P218020.1%
 
V211500.1%
 
Y160160.1%
 
H97140.1%
 
U89400.1%
 
Z6892< 0.1%
 
21983< 0.1%
 
Other values (2)3966< 0.1%
 
Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size14.3 MiB
ST/C&L
1377090 
FS
220497 
BIA
 
119943
BLM
 
97034
IA
 
21841
Other values (6)
 
44060
ValueCountFrequency (%) 
ST/C&L137709073.2%
 
FS22049711.7%
 
BIA1199436.4%
 
BLM970345.2%
 
IA218411.2%
 
NPS208931.1%
 
FWS193311.0%
 
TRIBE37390.2%
 
DOD81< 0.1%
 
BOR14< 0.1%
 
DOE2< 0.1%
 
2020-11-18T18:04:12.306874image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-18T18:04:12.412875image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length6
Mean length5.07204601
Min length2

Overview of Unicode Properties

Unique unicode characters18
Unique unicode categories2 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
S163781117.2%
 
L147412415.5%
 
T138082914.5%
 
/137709014.4%
 
C137709014.4%
 
&137709014.4%
 
F2398282.5%
 
B2207302.3%
 
I1455231.5%
 
A1417841.5%
 
M970341.0%
 
N208930.2%
 
P208930.2%
 
W193310.2%
 
R3753< 0.1%
 
E3741< 0.1%
 
D164< 0.1%
 
O97< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter678362571.1%
 
Other Punctuation275418028.9%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
S163781124.1%
 
L147412421.7%
 
T138082920.4%
 
C137709020.3%
 
F2398283.5%
 
B2207303.3%
 
I1455232.1%
 
A1417842.1%
 
M970341.4%
 
N208930.3%
 
P208930.3%
 
W193310.3%
 
R37530.1%
 
E37410.1%
 
D164< 0.1%
 
O97< 0.1%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/137709050.0%
 
&137709050.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin678362571.1%
 
Common275418028.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
S163781124.1%
 
L147412421.7%
 
T138082920.4%
 
C137709020.3%
 
F2398283.5%
 
B2207303.3%
 
I1455232.1%
 
A1417842.1%
 
M970341.4%
 
N208930.3%
 
P208930.3%
 
W193310.3%
 
R37530.1%
 
E37410.1%
 
D164< 0.1%
 
O97< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
/137709050.0%
 
&137709050.0%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII9537805100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
S163781117.2%
 
L147412415.5%
 
T138082914.5%
 
/137709014.4%
 
C137709014.4%
 
&137709014.4%
 
F2398282.5%
 
B2207302.3%
 
I1455231.5%
 
A1417841.5%
 
M970341.0%
 
N208930.2%
 
P208930.2%
 
W193310.2%
 
R3753< 0.1%
 
E3741< 0.1%
 
D164< 0.1%
 
O97< 0.1%
 

NWCG_REPORTING_UNIT_ID
Categorical

HIGH CARDINALITY

Distinct1640
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 MiB
USGAGAS
167123 
USTXTXS
 
111362
USNCNCS
 
107424
USFLFLS
 
83024
USSCSCS
 
78977
Other values (1635)
1332555 
ValueCountFrequency (%) 
USGAGAS1671238.9%
 
USTXTXS1113625.9%
 
USNCNCS1074245.7%
 
USFLFLS830244.4%
 
USSCSCS789774.2%
 
USNYNYX754614.0%
 
USMSMSS751174.0%
 
USALALS647053.4%
 
USOKOKS296821.6%
 
USMNMNS294321.6%
 
USTNTNS293931.6%
 
USWIWIS290621.5%
 
USARARS282731.5%
 
USLALAS274501.5%
 
USNJNJS258171.4%
 
USKYKYS249481.3%
 
USPRIITF218021.2%
 
USWVWVS215101.1%
 
USVAVAS204381.1%
 
USWAWAS173130.9%
 
USCARRU137980.7%
 
USAZAZS130990.7%
 
USMEMES129560.7%
 
USMOMOS128730.7%
 
USCAMMU123550.7%
 
Other values (1615)74707139.7%
 
2020-11-18T18:04:12.557875image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique197 ?
Unique (%)< 0.1%
2020-11-18T18:04:12.693875image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length9
Median length7
Mean length7.0303409
Min length7

Overview of Unicode Properties

Unique unicode characters36
Unique unicode categories2 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
S351393926.6%
 
U205972215.6%
 
A11974719.1%
 
N8109956.1%
 
C7526225.7%
 
T5073033.8%
 
M5058333.8%
 
F4663803.5%
 
L4337683.3%
 
G3640192.8%
 
X3387212.6%
 
R2644592.0%
 
O2629742.0%
 
Y2447421.9%
 
D2322861.8%
 
I2234861.7%
 
W2172471.6%
 
K1809911.4%
 
V1191750.9%
 
P1075350.8%
 
Z945240.7%
 
E841420.6%
 
H640990.5%
 
J609060.5%
 
B565180.4%
 
Other values (11)564530.4%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter1316629099.6%
 
Decimal Number540200.4%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
S351393926.7%
 
U205972215.6%
 
A11974719.1%
 
N8109956.2%
 
C7526225.7%
 
T5073033.9%
 
M5058333.8%
 
F4663803.5%
 
L4337683.3%
 
G3640192.8%
 
X3387212.6%
 
R2644592.0%
 
O2629742.0%
 
Y2447421.9%
 
D2322861.8%
 
I2234861.7%
 
W2172471.7%
 
K1809911.4%
 
V1191750.9%
 
P1075350.8%
 
Z945240.7%
 
E841420.6%
 
H640990.5%
 
J609060.5%
 
B565180.4%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
11091220.2%
 
71068419.8%
 
5795514.7%
 
2710913.2%
 
9674412.5%
 
836876.8%
 
333766.2%
 
022934.2%
 
411882.2%
 
6720.1%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin1316629099.6%
 
Common540200.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
S351393926.7%
 
U205972215.6%
 
A11974719.1%
 
N8109956.2%
 
C7526225.7%
 
T5073033.9%
 
M5058333.8%
 
F4663803.5%
 
L4337683.3%
 
G3640192.8%
 
X3387212.6%
 
R2644592.0%
 
O2629742.0%
 
Y2447421.9%
 
D2322861.8%
 
I2234861.7%
 
W2172471.7%
 
K1809911.4%
 
V1191750.9%
 
P1075350.8%
 
Z945240.7%
 
E841420.6%
 
H640990.5%
 
J609060.5%
 
B565180.4%
 

Most frequent Common characters

ValueCountFrequency (%) 
11091220.2%
 
71068419.8%
 
5795514.7%
 
2710913.2%
 
9674412.5%
 
836876.8%
 
333766.2%
 
022934.2%
 
411882.2%
 
6720.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII13220310100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
S351393926.6%
 
U205972215.6%
 
A11974719.1%
 
N8109956.1%
 
C7526225.7%
 
T5073033.8%
 
M5058333.8%
 
F4663803.5%
 
L4337683.3%
 
G3640192.8%
 
X3387212.6%
 
R2644592.0%
 
O2629742.0%
 
Y2447421.9%
 
D2322861.8%
 
I2234861.7%
 
W2172471.6%
 
K1809911.4%
 
V1191750.9%
 
P1075350.8%
 
Z945240.7%
 
E841420.6%
 
H640990.5%
 
J609060.5%
 
B565180.4%
 
Other values (11)564530.4%
 

NWCG_REPORTING_UNIT_NAME
Categorical

HIGH CARDINALITY

Distinct1635
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 MiB
Georgia Forestry Commission
167123 
Texas A & M Forest Service
 
111362
North Carolina Forest Service
 
107424
Florida Forest Service
 
83024
South Carolina Forestry Commission
 
78977
Other values (1630)
1332555 
ValueCountFrequency (%) 
Georgia Forestry Commission1671238.9%
 
Texas A & M Forest Service1113625.9%
 
North Carolina Forest Service1074245.7%
 
Florida Forest Service830244.4%
 
South Carolina Forestry Commission789774.2%
 
Fire Department of New York754614.0%
 
Mississippi Forestry Commission751174.0%
 
Alabama Forestry Commission647053.4%
 
Oklahoma Division of Forestry296821.6%
 
Minnesota Department of Natural Resources294321.6%
 
Tennessee Division of Forestry293931.6%
 
Wisconsin Department of Natural Resources290621.5%
 
Arkansas Forestry Commission282731.5%
 
Louisiana Office of Forestry274501.5%
 
New Jersey Forest Fire Service258171.4%
 
Kentucky Division of Forestry249481.3%
 
International Institute of Tropical Forestry218021.2%
 
West Virginia Division of Forestry215101.1%
 
Virginia Department of Forestry204381.1%
 
Washington State Headquarters173130.9%
 
Riverside Unit137980.7%
 
Arizona State Forestry Division - State Office130990.7%
 
Maine Forest Service129560.7%
 
Missouri Department of Conservation128730.7%
 
Merced-Mariposa Unit123550.7%
 
Other values (1610)74707139.7%
 
2020-11-18T18:04:12.844876image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique195 ?
Unique (%)< 0.1%
2020-11-18T18:04:13.004850image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length79
Median length27
Mean length27.3905651
Min length5

Overview of Unicode Properties

Unique unicode characters66
Unique unicode categories8 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
519854810.1%
 
e47407359.2%
 
o45331958.8%
 
r42640698.3%
 
i42106588.2%
 
s37106667.2%
 
t33382366.5%
 
a33180456.4%
 
n25847985.0%
 
F15717893.1%
 
m12301482.4%
 
l11704342.3%
 
c9772721.9%
 
y9014101.8%
 
C7790081.5%
 
S6741321.3%
 
f6436631.2%
 
N6235521.2%
 
v6183871.2%
 
u5458081.1%
 
D4697790.9%
 
p4637620.9%
 
g4488110.9%
 
h4349260.8%
 
d4127430.8%
 
Other values (41)36424257.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter3936924976.4%
 
Uppercase Letter663359912.9%
 
Space Separator519854810.1%
 
Dash Punctuation1657730.3%
 
Other Punctuation1396370.3%
 
Open Punctuation85< 0.1%
 
Close Punctuation85< 0.1%
 
Decimal Number23< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
F157178923.7%
 
C77900811.7%
 
S67413210.2%
 
N6235529.4%
 
D4697797.1%
 
A4042926.1%
 
M3757825.7%
 
T2600903.9%
 
G1992083.0%
 
R1737502.6%
 
O1558782.3%
 
U1474522.2%
 
W1365372.1%
 
L1149081.7%
 
P933241.4%
 
Y915381.4%
 
I703131.1%
 
H640451.0%
 
V603790.9%
 
B558310.8%
 
K557410.8%
 
J328890.5%
 
E185790.3%
 
Z45770.1%
 
Q226< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
e474073512.0%
 
o453319511.5%
 
r426406910.8%
 
i421065810.7%
 
s37106669.4%
 
t33382368.5%
 
a33180458.4%
 
n25847986.6%
 
m12301483.1%
 
l11704343.0%
 
c9772722.5%
 
y9014102.3%
 
f6436631.6%
 
v6183871.6%
 
u5458081.4%
 
p4637621.2%
 
g4488111.1%
 
h4349261.1%
 
d4127431.0%
 
k2785970.7%
 
w1900080.5%
 
x1563030.4%
 
b1358480.3%
 
q287540.1%
 
z278430.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
5198548100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-165773100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
&11829384.7%
 
/115628.3%
 
.49813.6%
 
'47703.4%
 
"16< 0.1%
 
#15< 0.1%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(85100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)85100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
41043.5%
 
1939.1%
 
528.7%
 
614.3%
 
014.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin4600284889.3%
 
Common550415110.7%
 

Most frequent Latin characters

ValueCountFrequency (%) 
e474073510.3%
 
o45331959.9%
 
r42640699.3%
 
i42106589.2%
 
s37106668.1%
 
t33382367.3%
 
a33180457.2%
 
n25847985.6%
 
F15717893.4%
 
m12301482.7%
 
l11704342.5%
 
c9772722.1%
 
y9014102.0%
 
C7790081.7%
 
S6741321.5%
 
f6436631.4%
 
N6235521.4%
 
v6183871.3%
 
u5458081.2%
 
D4697791.0%
 
p4637621.0%
 
g4488111.0%
 
h4349260.9%
 
d4127430.9%
 
A4042920.9%
 
Other values (26)29325306.4%
 

Most frequent Common characters

ValueCountFrequency (%) 
519854894.4%
 
-1657733.0%
 
&1182932.1%
 
/115620.2%
 
.49810.1%
 
'47700.1%
 
(85< 0.1%
 
)85< 0.1%
 
"16< 0.1%
 
#15< 0.1%
 
410< 0.1%
 
19< 0.1%
 
52< 0.1%
 
61< 0.1%
 
01< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII51506999100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
519854810.1%
 
e47407359.2%
 
o45331958.8%
 
r42640698.3%
 
i42106588.2%
 
s37106667.2%
 
t33382366.5%
 
a33180456.4%
 
n25847985.0%
 
F15717893.1%
 
m12301482.4%
 
l11704342.3%
 
c9772721.9%
 
y9014101.8%
 
C7790081.5%
 
S6741321.3%
 
f6436631.2%
 
N6235521.2%
 
v6183871.2%
 
u5458081.1%
 
D4697790.9%
 
p4637620.9%
 
g4488110.9%
 
h4349260.8%
 
d4127430.8%
 
Other values (41)36424257.1%
 

SOURCE_REPORTING_UNIT
Categorical

HIGH CARDINALITY

Distinct4992
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.3 MiB
GAGAS
 
97844
SCSCS
 
52064
TXTXS
 
40366
FLFLS
 
37945
NCNCS
 
37255
Other values (4987)
1614991 
ValueCountFrequency (%) 
GAGAS978445.2%
 
SCSCS520642.8%
 
TXTXS403662.1%
 
FLFLS379452.0%
 
NCNCS372552.0%
 
TXVFD362661.9%
 
MSMSS318221.7%
 
MNMNS239141.3%
 
PRIITF218021.2%
 
WVDOF170880.9%
 
TXSFD154610.8%
 
CARRU137980.7%
 
OKOKS135920.7%
 
AZAZS130940.7%
 
TXLFDX129070.7%
 
CAMMU123550.7%
 
KYKYS116610.6%
 
WAWAS115280.6%
 
ALALS114090.6%
 
VAVAS103230.5%
 
MOMOS99080.5%
 
MEMES97930.5%
 
WIWIS96300.5%
 
NCNCS20691570.5%
 
MNRLA91540.5%
 
Other values (4967)131032969.7%
 
2020-11-18T18:04:13.184848image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique619 ?
Unique (%)< 0.1%
2020-11-18T18:04:13.355878image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length21
Median length5
Mean length5.572214851
Min length2

Overview of Unicode Properties

Unique unicode characters63
Unique unicode categories7 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
S123376811.8%
 
A10224669.8%
 
C6990236.7%
 
N6360606.1%
 
04751234.5%
 
L4032553.8%
 
F3943553.8%
 
M3916823.7%
 
T3821303.6%
 
D3507143.3%
 
G3121203.0%
 
13120973.0%
 
R2617232.5%
 
O2237132.1%
 
X2051532.0%
 
21972931.9%
 
Y1697221.6%
 
31631451.6%
 
U1614271.5%
 
K1588021.5%
 
W1499341.4%
 
I1425491.4%
 
V1365511.3%
 
41355261.3%
 
51318311.3%
 
Other values (38)162819315.5%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter784795774.9%
 
Decimal Number172469116.5%
 
Lowercase Letter7585537.2%
 
Space Separator1235721.2%
 
Dash Punctuation215450.2%
 
Connector Punctuation2030< 0.1%
 
Other Punctuation7< 0.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
047512327.5%
 
131209718.1%
 
219729311.4%
 
31631459.5%
 
41355267.9%
 
51318317.6%
 
61066096.2%
 
8798424.6%
 
7650413.8%
 
9581843.4%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
S123376815.7%
 
A102246613.0%
 
C6990238.9%
 
N6360608.1%
 
L4032555.1%
 
F3943555.0%
 
M3916825.0%
 
T3821304.9%
 
D3507144.5%
 
G3121204.0%
 
R2617233.3%
 
O2237132.9%
 
X2051532.6%
 
Y1697222.2%
 
U1614272.1%
 
K1588022.0%
 
W1499341.9%
 
I1425491.8%
 
V1365511.7%
 
P967851.2%
 
E826461.1%
 
Z653890.8%
 
B653640.8%
 
J554730.7%
 
H467500.6%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
t8724311.5%
 
e8697311.5%
 
a8517511.2%
 
s658858.7%
 
o638588.4%
 
l533827.0%
 
i487476.4%
 
r431095.7%
 
h388155.1%
 
u323734.3%
 
n321584.2%
 
c310174.1%
 
p200762.6%
 
m144061.9%
 
w114781.5%
 
g111261.5%
 
v89841.2%
 
d87561.2%
 
y58920.8%
 
b53030.7%
 
f22320.3%
 
k15630.2%
 
q2< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
123572100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-21545100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/7100.0%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_2030100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin860651082.1%
 
Common187184517.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
047512325.4%
 
131209716.7%
 
219729310.5%
 
31631458.7%
 
41355267.2%
 
51318317.0%
 
1235726.6%
 
61066095.7%
 
8798424.3%
 
7650413.5%
 
9581843.1%
 
-215451.2%
 
_20300.1%
 
/7< 0.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
S123376814.3%
 
A102246611.9%
 
C6990238.1%
 
N6360607.4%
 
L4032554.7%
 
F3943554.6%
 
M3916824.6%
 
T3821304.4%
 
D3507144.1%
 
G3121203.6%
 
R2617233.0%
 
O2237132.6%
 
X2051532.4%
 
Y1697222.0%
 
U1614271.9%
 
K1588021.8%
 
W1499341.7%
 
I1425491.7%
 
V1365511.6%
 
P967851.1%
 
t872431.0%
 
e869731.0%
 
a851751.0%
 
E826461.0%
 
s658850.8%
 
Other values (24)6666567.7%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII10478355100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
S123376811.8%
 
A10224669.8%
 
C6990236.7%
 
N6360606.1%
 
04751234.5%
 
L4032553.8%
 
F3943553.8%
 
M3916823.7%
 
T3821303.6%
 
D3507143.3%
 
G3121203.0%
 
13120973.0%
 
R2617232.5%
 
O2237132.1%
 
X2051532.0%
 
21972931.9%
 
Y1697221.6%
 
31631451.6%
 
U1614271.5%
 
K1588021.5%
 
W1499341.4%
 
I1425491.4%
 
V1365511.3%
 
41355261.3%
 
51318311.3%
 
Other values (38)162819315.5%
 

SOURCE_REPORTING_UNIT_NAME
Categorical

HIGH CARDINALITY

Distinct4441
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.3 MiB
Georgia Forestry Commission
 
97844
Fire Department of New York
 
75461
South Carolina Forestry Commission
 
52064
Mississippi Forestry Commission
 
46396
Texas Forest Service
 
42675
Other values (4436)
1566025 
ValueCountFrequency (%) 
Georgia Forestry Commission978445.2%
 
Fire Department of New York754614.0%
 
South Carolina Forestry Commission520642.8%
 
Mississippi Forestry Commission463962.5%
 
Texas Forest Service426752.3%
 
North Carolina Division of Forest Resources398792.1%
 
Florida Forest Service379452.0%
 
Minnesota Department of Natural Resources294321.6%
 
International Institute of Tropical Forestry218021.2%
 
Alabama Forestry Commission211331.1%
 
West Virginia Division of Forestry198141.1%
 
Wisconsin Department of Natural Resources142100.8%
 
CDF - Riverside Unit137980.7%
 
Oklahoma Division of Forestry135920.7%
 
Local Fire Department132430.7%
 
Arizona State Forestry Division - State Office130940.7%
 
Maine Forest Service129560.7%
 
Kentucky Division of Forestry128670.7%
 
Virginia Department of Forestry124440.7%
 
CDF - Merced-Mariposa Unit123550.7%
 
Washington State Headquarters115280.6%
 
New Mexico - State Forestry111440.6%
 
Arkansas Forestry Commission108230.6%
 
Missouri Department of Conservation99080.5%
 
NCS Region 2 District 691570.5%
 
Other values (4416)122490165.1%
 
2020-11-18T18:04:13.505874image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique604 ?
Unique (%)< 0.1%
2020-11-18T18:04:13.645848image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length74
Median length26
Mean length25.9990061
Min length5

Overview of Unicode Properties

Unique unicode characters76
Unique unicode categories9 ?
Unique unicode scripts2 ?
Unique unicode blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
514051610.5%
 
e43343338.9%
 
i40137598.2%
 
o36391957.4%
 
r35865827.3%
 
t35793817.3%
 
s30312716.2%
 
a28818185.9%
 
n25149505.1%
 
F13231322.7%
 
l11835312.4%
 
c11829142.4%
 
S8673071.8%
 
D8557831.8%
 
m8494801.7%
 
C7777431.6%
 
y6880901.4%
 
f6450871.3%
 
N6341471.3%
 
u6017451.2%
 
g4871091.0%
 
p4658881.0%
 
v4494280.9%
 
A4353480.9%
 
h4096110.8%
 
Other values (51)43120738.8%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter3566474172.9%
 
Uppercase Letter742990415.2%
 
Space Separator514051610.5%
 
Decimal Number3195860.7%
 
Dash Punctuation2190600.4%
 
Other Punctuation878230.2%
 
Open Punctuation14254< 0.1%
 
Close Punctuation14253< 0.1%
 
Modifier Symbol84< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
F132313217.8%
 
S86730711.7%
 
D85578311.5%
 
C77774310.5%
 
N6341478.5%
 
A4353485.9%
 
R3257254.4%
 
M2854933.8%
 
U2151292.9%
 
G2144362.9%
 
O2124602.9%
 
T2076482.8%
 
L1862032.5%
 
W1608622.2%
 
P1120781.5%
 
Y1059811.4%
 
B966931.3%
 
V937351.3%
 
K819651.1%
 
I791261.1%
 
H611080.8%
 
E510460.7%
 
J413220.6%
 
Z46150.1%
 
Q528< 0.1%
 
Other values (2)291< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
e433433312.2%
 
i401375911.3%
 
o363919510.2%
 
r358658210.1%
 
t357938110.0%
 
s30312718.5%
 
a28818188.1%
 
n25149507.1%
 
l11835313.3%
 
c11829143.3%
 
m8494802.4%
 
y6880901.9%
 
f6450871.8%
 
u6017451.7%
 
g4871091.4%
 
p4658881.3%
 
v4494281.3%
 
h4096111.1%
 
d3964061.1%
 
k2829270.8%
 
w1924850.5%
 
b1062350.3%
 
x939760.3%
 
z257720.1%
 
q186440.1%
 
Other values (2)4124< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
5140516100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-219060100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
,5908967.3%
 
.1801920.5%
 
&62737.1%
 
/17562.0%
 
'16481.9%
 
#10241.2%
 
"14< 0.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
28188225.6%
 
16564920.5%
 
35866418.4%
 
4269608.4%
 
6201736.3%
 
5185555.8%
 
0144514.5%
 
8136504.3%
 
998493.1%
 
797533.1%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(14254100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)14253100.0%
 

Most frequent Modifier Symbol characters

ValueCountFrequency (%) 
`84100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin4309464588.1%
 
Common579557611.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
e433433310.1%
 
i40137599.3%
 
o36391958.4%
 
r35865828.3%
 
t35793818.3%
 
s30312717.0%
 
a28818186.7%
 
n25149505.8%
 
F13231323.1%
 
l11835312.7%
 
c11829142.7%
 
S8673072.0%
 
D8557832.0%
 
m8494802.0%
 
C7777431.8%
 
y6880901.6%
 
f6450871.5%
 
N6341471.5%
 
u6017451.4%
 
g4871091.1%
 
p4658881.1%
 
v4494281.0%
 
A4353481.0%
 
h4096111.0%
 
d3964060.9%
 
Other values (29)32606077.6%
 

Most frequent Common characters

ValueCountFrequency (%) 
514051688.7%
 
-2190603.8%
 
2818821.4%
 
1656491.1%
 
,590891.0%
 
3586641.0%
 
4269600.5%
 
6201730.3%
 
5185550.3%
 
.180190.3%
 
0144510.2%
 
(142540.2%
 
)142530.2%
 
8136500.2%
 
998490.2%
 
797530.2%
 
&62730.1%
 
/1756< 0.1%
 
'1648< 0.1%
 
#1024< 0.1%
 
`84< 0.1%
 
"14< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII48890183> 99.9%
 
None38< 0.1%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
514051610.5%
 
e43343338.9%
 
i40137598.2%
 
o36391957.4%
 
r35865827.3%
 
t35793817.3%
 
s30312716.2%
 
a28818185.9%
 
n25149505.1%
 
F13231322.7%
 
l11835312.4%
 
c11829142.4%
 
S8673071.8%
 
D8557831.8%
 
m8494801.7%
 
C7777431.6%
 
y6880901.4%
 
f6450871.3%
 
N6341471.3%
 
u6017451.2%
 
g4871091.0%
 
p4658881.0%
 
v4494280.9%
 
A4353480.9%
 
h4096110.8%
 
Other values (49)43120358.8%
 

Most frequent None characters

ValueCountFrequency (%) 
ñ3797.4%
 
Æ12.6%
 

LOCAL_FIRE_REPORT_ID
Categorical

HIGH CARDINALITY
MISSING

Distinct13508
Distinct (%)3.2%
Missing1459286
Missing (%)77.6%
Memory size14.3 MiB
001
 
8189
002
 
4960
1
 
3652
2
 
3554
3
 
3494
Other values (13503)
397330 
ValueCountFrequency (%) 
00181890.4%
 
00249600.3%
 
136520.2%
 
235540.2%
 
334940.2%
 
534330.2%
 
434230.2%
 
00333440.2%
 
633310.2%
 
733100.2%
 
832950.2%
 
932140.2%
 
1031930.2%
 
1131680.2%
 
1231290.2%
 
1330920.2%
 
1430570.2%
 
1529910.2%
 
1629820.2%
 
1729620.2%
 
1829100.2%
 
1928620.2%
 
2028280.2%
 
2128030.1%
 
2227820.1%
 
Other values (13483)33522117.8%
 
(Missing)145928677.6%
 
2020-11-18T18:04:13.810874image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique9939 ?
Unique (%)2.4%
2020-11-18T18:04:13.923874image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length3
Mean length2.888274443
Min length1

Overview of Unicode Properties

Unique unicode characters32
Unique unicode categories4 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n291857253.7%
 
a145928726.9%
 
11915913.5%
 
01580252.9%
 
21270702.3%
 
31041731.9%
 
4962121.8%
 
5868991.6%
 
6783821.4%
 
7728241.3%
 
8686371.3%
 
9680311.3%
 
A242< 0.1%
 
B240< 0.1%
 
C177< 0.1%
 
D119< 0.1%
 
T94< 0.1%
 
F93< 0.1%
 
E82< 0.1%
 
P77< 0.1%
 
H71< 0.1%
 
J71< 0.1%
 
R56< 0.1%
 
L54< 0.1%
 
M52< 0.1%
 
Other values (7)168< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter437785980.6%
 
Decimal Number105184419.4%
 
Uppercase Letter1595< 0.1%
 
Dash Punctuation1< 0.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
119159118.2%
 
015802515.0%
 
212707012.1%
 
31041739.9%
 
4962129.1%
 
5868998.3%
 
6783827.5%
 
7728246.9%
 
8686376.5%
 
9680316.5%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n291857266.7%
 
a145928733.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
A24215.2%
 
B24015.0%
 
C17711.1%
 
D1197.5%
 
T945.9%
 
F935.8%
 
E825.1%
 
P774.8%
 
H714.5%
 
J714.5%
 
R563.5%
 
L543.4%
 
M523.3%
 
S432.7%
 
K412.6%
 
V402.5%
 
W311.9%
 
G110.7%
 
O10.1%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-1100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin437945480.6%
 
Common105184519.4%
 

Most frequent Common characters

ValueCountFrequency (%) 
119159118.2%
 
015802515.0%
 
212707012.1%
 
31041739.9%
 
4962129.1%
 
5868998.3%
 
6783827.5%
 
7728246.9%
 
8686376.5%
 
9680316.5%
 
-1< 0.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n291857266.6%
 
a145928733.3%
 
A242< 0.1%
 
B240< 0.1%
 
C177< 0.1%
 
D119< 0.1%
 
T94< 0.1%
 
F93< 0.1%
 
E82< 0.1%
 
P77< 0.1%
 
H71< 0.1%
 
J71< 0.1%
 
R56< 0.1%
 
L54< 0.1%
 
M52< 0.1%
 
S43< 0.1%
 
K41< 0.1%
 
V40< 0.1%
 
W31< 0.1%
 
G11< 0.1%
 
O1< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII5431299100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n291857253.7%
 
a145928726.9%
 
11915913.5%
 
01580252.9%
 
21270702.3%
 
31041731.9%
 
4962121.8%
 
5868991.6%
 
6783821.4%
 
7728241.3%
 
8686371.3%
 
9680311.3%
 
A242< 0.1%
 
B240< 0.1%
 
C177< 0.1%
 
D119< 0.1%
 
T94< 0.1%
 
F93< 0.1%
 
E82< 0.1%
 
P77< 0.1%
 
H71< 0.1%
 
J71< 0.1%
 
R56< 0.1%
 
L54< 0.1%
 
M52< 0.1%
 
Other values (7)168< 0.1%
 

LOCAL_INCIDENT_ID
Categorical

HIGH CARDINALITY
MISSING

Distinct565914
Distinct (%)53.4%
Missing820821
Missing (%)43.6%
Memory size14.3 MiB
001
 
3839
1
 
3258
2
 
2874
3
 
2647
002
 
2489
Other values (565909)
1044537 
ValueCountFrequency (%) 
00138390.2%
 
132580.2%
 
228740.2%
 
326470.1%
 
00224890.1%
 
424290.1%
 
522610.1%
 
1022080.1%
 
621500.1%
 
1120820.1%
 
720250.1%
 
1219950.1%
 
819390.1%
 
1318740.1%
 
00318430.1%
 
918180.1%
 
1418080.1%
 
1517160.1%
 
1616810.1%
 
1716130.1%
 
1815660.1%
 
1915020.1%
 
00414800.1%
 
2014310.1%
 
2113900.1%
 
Other values (565889)100772653.6%
 
(Missing)82082143.6%
 
2020-11-18T18:04:16.829848image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique501595 ?
Unique (%)47.3%
2020-11-18T18:04:16.983881image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length28
Median length3
Mean length5.901776422
Min length1

Overview of Unicode Properties

Unique unicode characters76
Unique unicode categories11 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
0175692415.8%
 
n166896915.0%
 
19250908.3%
 
a8470427.6%
 
28112357.3%
 
5666245.1%
 
-5529705.0%
 
35082584.6%
 
44760784.3%
 
54493584.0%
 
93983913.6%
 
63627403.3%
 
73545653.2%
 
83516293.2%
 
Y1279901.2%
 
N1070691.0%
 
F804740.7%
 
A579730.5%
 
S534900.5%
 
C468710.4%
 
.412050.4%
 
T342430.3%
 
M340870.3%
 
e313330.3%
 
L291860.3%
 
Other values (51)4242903.8%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number639426857.6%
 
Lowercase Letter274227724.7%
 
Uppercase Letter7766657.0%
 
Space Separator5666245.1%
 
Dash Punctuation5529705.0%
 
Other Punctuation559340.5%
 
Open Punctuation4199< 0.1%
 
Close Punctuation4199< 0.1%
 
Connector Punctuation944< 0.1%
 
Math Symbol3< 0.1%
 
Modifier Symbol1< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
Y12799016.5%
 
N10706913.8%
 
F8047410.4%
 
A579737.5%
 
S534906.9%
 
C468716.0%
 
T342434.4%
 
M340874.4%
 
L291863.8%
 
U289783.7%
 
B258163.3%
 
R240583.1%
 
W190572.5%
 
E154672.0%
 
D126211.6%
 
X113141.5%
 
H108801.4%
 
Z88841.1%
 
P88081.1%
 
O85991.1%
 
V66410.9%
 
G63590.8%
 
K57530.7%
 
I57320.7%
 
J44130.6%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-552970100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
0175692427.5%
 
192509014.5%
 
281123512.7%
 
35082587.9%
 
44760787.4%
 
54493587.0%
 
93983916.2%
 
63627405.7%
 
73545655.5%
 
83516295.5%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n166896960.9%
 
a84704230.9%
 
e313331.1%
 
o267401.0%
 
r249110.9%
 
l210560.8%
 
i165760.6%
 
t153780.6%
 
s130060.5%
 
h97570.4%
 
u94820.3%
 
c76930.3%
 
k69470.3%
 
f68660.3%
 
d63630.2%
 
g60920.2%
 
y59280.2%
 
m55970.2%
 
w42030.2%
 
p37320.1%
 
b24470.1%
 
v1261< 0.1%
 
q499< 0.1%
 
x394< 0.1%
 
z3< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
566624100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.4120573.7%
 
/1359224.3%
 
,10261.8%
 
#1000.2%
 
?9< 0.1%
 
*1< 0.1%
 
@1< 0.1%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_944100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(4199100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)4199100.0%
 

Most frequent Math Symbol characters

ValueCountFrequency (%) 
=3100.0%
 

Most frequent Modifier Symbol characters

ValueCountFrequency (%) 
`1100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common757914268.3%
 
Latin351894231.7%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n166896947.4%
 
a84704224.1%
 
Y1279903.6%
 
N1070693.0%
 
F804742.3%
 
A579731.6%
 
S534901.5%
 
C468711.3%
 
T342431.0%
 
M340871.0%
 
e313330.9%
 
L291860.8%
 
U289780.8%
 
o267400.8%
 
B258160.7%
 
r249110.7%
 
R240580.7%
 
l210560.6%
 
W190570.5%
 
i165760.5%
 
E154670.4%
 
t153780.4%
 
s130060.4%
 
D126210.4%
 
X113140.3%
 
Other values (27)1452374.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
0175692423.2%
 
192509012.2%
 
281123510.7%
 
5666247.5%
 
-5529707.3%
 
35082586.7%
 
44760786.3%
 
54493585.9%
 
93983915.3%
 
63627404.8%
 
73545654.7%
 
83516294.6%
 
.412050.5%
 
/135920.2%
 
(41990.1%
 
)41990.1%
 
,1026< 0.1%
 
_944< 0.1%
 
#100< 0.1%
 
?9< 0.1%
 
=3< 0.1%
 
`1< 0.1%
 
*1< 0.1%
 
@1< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII11098084100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
0175692415.8%
 
n166896915.0%
 
19250908.3%
 
a8470427.6%
 
28112357.3%
 
5666245.1%
 
-5529705.0%
 
35082584.6%
 
44760784.3%
 
54493584.0%
 
93983913.6%
 
63627403.3%
 
73545653.2%
 
83516293.2%
 
Y1279901.2%
 
N1070691.0%
 
F804740.7%
 
A579730.5%
 
S534900.5%
 
C468710.4%
 
.412050.4%
 
T342430.3%
 
M340870.3%
 
e313330.3%
 
L291860.3%
 
Other values (51)4242903.8%
 

FIRE_CODE
Categorical

HIGH CARDINALITY
MISSING

Distinct172446
Distinct (%)53.1%
Missing1555636
Missing (%)82.7%
Memory size14.3 MiB
D44Z
 
9451
5555
 
5144
D5GJ
 
3459
0001
 
3329
0000
 
1928
Other values (172441)
301518 
ValueCountFrequency (%) 
D44Z94510.5%
 
555551440.3%
 
D5GJ34590.2%
 
000133290.2%
 
000019280.1%
 
230018920.1%
 
EKV310320.1%
 
470010030.1%
 
EKW0938< 0.1%
 
0100904< 0.1%
 
EKT5883< 0.1%
 
5900833< 0.1%
 
EKV0756< 0.1%
 
EK2R729< 0.1%
 
7000721< 0.1%
 
EKV5703< 0.1%
 
EK2D690< 0.1%
 
EK3D666< 0.1%
 
EK2N660< 0.1%
 
EKV6647< 0.1%
 
EK2A624< 0.1%
 
EKT4614< 0.1%
 
EK2B585< 0.1%
 
EK2Q551< 0.1%
 
7500537< 0.1%
 
Other values (172421)28555015.2%
 
(Missing)155563682.7%
 
2020-11-18T18:04:17.760885image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique148058 ?
Unique (%)45.6%
2020-11-18T18:04:17.906882image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length3
Mean length3.17233663
Min length0

Overview of Unicode Properties

Unique unicode characters53
Unique unicode categories10 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n311127352.2%
 
a155563626.1%
 
01045771.8%
 
5782201.3%
 
4729771.2%
 
E708431.2%
 
1649011.1%
 
6639971.1%
 
2634811.1%
 
3559890.9%
 
D516950.9%
 
7509890.9%
 
8498860.8%
 
K457520.8%
 
9454100.8%
 
B436280.7%
 
C390650.7%
 
G331230.6%
 
F318580.5%
 
H310790.5%
 
J309470.5%
 
A292240.5%
 
Z270330.5%
 
V247850.4%
 
T193030.3%
 
Other values (28)1697972.8%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter466692878.2%
 
Decimal Number65042710.9%
 
Uppercase Letter64805010.9%
 
Other Punctuation37< 0.1%
 
Dash Punctuation12< 0.1%
 
Modifier Symbol3< 0.1%
 
Currency Symbol3< 0.1%
 
Space Separator3< 0.1%
 
Close Punctuation3< 0.1%
 
Open Punctuation2< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
E7084310.9%
 
D516958.0%
 
K457527.1%
 
B436286.7%
 
C390656.0%
 
G331235.1%
 
F318584.9%
 
H310794.8%
 
J309474.8%
 
A292244.5%
 
Z270334.2%
 
V247853.8%
 
T193033.0%
 
W182522.8%
 
U178322.8%
 
N158632.4%
 
R157222.4%
 
S151952.3%
 
X151092.3%
 
Y149872.3%
 
P142832.2%
 
L142812.2%
 
Q141562.2%
 
M140352.2%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
010457716.1%
 
57822012.0%
 
47297711.2%
 
16490110.0%
 
6639979.8%
 
2634819.8%
 
3559898.6%
 
7509897.8%
 
8498867.7%
 
9454107.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n311127366.7%
 
a155563633.3%
 
e9< 0.1%
 
b9< 0.1%
 
u1< 0.1%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/2978.4%
 
@25.4%
 
&25.4%
 
!12.7%
 
.12.7%
 
*12.7%
 
:12.7%
 

Most frequent Modifier Symbol characters

ValueCountFrequency (%) 
^266.7%
 
`133.3%
 

Most frequent Currency Symbol characters

ValueCountFrequency (%) 
$3100.0%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
3100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-12100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(2100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)3100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin531497889.1%
 
Common65049010.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n311127358.5%
 
a155563629.3%
 
E708431.3%
 
D516951.0%
 
K457520.9%
 
B436280.8%
 
C390650.7%
 
G331230.6%
 
F318580.6%
 
H310790.6%
 
J309470.6%
 
A292240.5%
 
Z270330.5%
 
V247850.5%
 
T193030.4%
 
W182520.3%
 
U178320.3%
 
N158630.3%
 
R157220.3%
 
S151950.3%
 
X151090.3%
 
Y149870.3%
 
P142830.3%
 
L142810.3%
 
Q141560.3%
 
Other values (4)140540.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
010457716.1%
 
57822012.0%
 
47297711.2%
 
16490110.0%
 
6639979.8%
 
2634819.8%
 
3559898.6%
 
7509897.8%
 
8498867.7%
 
9454107.0%
 
/29< 0.1%
 
-12< 0.1%
 
$3< 0.1%
 
3< 0.1%
 
)3< 0.1%
 
^2< 0.1%
 
@2< 0.1%
 
(2< 0.1%
 
&2< 0.1%
 
!1< 0.1%
 
.1< 0.1%
 
*1< 0.1%
 
`1< 0.1%
 
:1< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII5965468100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n311127352.2%
 
a155563626.1%
 
01045771.8%
 
5782201.3%
 
4729771.2%
 
E708431.2%
 
1649011.1%
 
6639971.1%
 
2634811.1%
 
3559890.9%
 
D516950.9%
 
7509890.9%
 
8498860.8%
 
K457520.8%
 
9454100.8%
 
B436280.7%
 
C390650.7%
 
G331230.6%
 
F318580.5%
 
H310790.5%
 
J309470.5%
 
A292240.5%
 
Z270330.5%
 
V247850.4%
 
T193030.3%
 
Other values (28)1697972.8%
 

FIRE_NAME
Categorical

HIGH CARDINALITY
MISSING

Distinct493633
Distinct (%)53.5%
Missing957189
Missing (%)50.9%
Memory size14.3 MiB
GRASS FIRE
 
3983
NA
 
3214
UNKNOWN
 
3154
LOCAL
 
2068
STATE
 
1423
Other values (493628)
909434 
ValueCountFrequency (%) 
GRASS FIRE39830.2%
 
NA32140.2%
 
UNKNOWN31540.2%
 
LOCAL 20680.1%
 
STATE 14230.1%
 
LOCAL FIRE 726< 0.1%
 
COTTONWOOD710< 0.1%
 
POWERLINE660< 0.1%
 
ROCK629< 0.1%
 
BEAR595< 0.1%
 
LOCAL595< 0.1%
 
WILLOW574< 0.1%
 
RIVER529< 0.1%
 
LAKE511< 0.1%
 
CANYON502< 0.1%
 
SPRING495< 0.1%
 
CREEK487< 0.1%
 
RIDGE483< 0.1%
 
LOST476< 0.1%
 
HORSE473< 0.1%
 
BRIDGE463< 0.1%
 
GRASS458< 0.1%
 
PINE451< 0.1%
 
RAILROAD419< 0.1%
 
CAMP405< 0.1%
 
Other values (493608)89879347.8%
 
(Missing)95718950.9%
 
2020-11-18T18:04:20.986847image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique414265 ?
Unique (%)44.9%
2020-11-18T18:04:21.138875image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length70
Median length3
Mean length7.187642418
Min length1

Overview of Unicode Properties

Unique unicode characters77
Unique unicode categories13 ?
Unique unicode scripts2 ?
Unique unicode blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
196697514.6%
 
n191437814.2%
 
a9571897.1%
 
E7658405.7%
 
R6703305.0%
 
A5726194.2%
 
O4920483.6%
 
N4542133.4%
 
I4502343.3%
 
L4396483.3%
 
S3813032.8%
 
T3704952.7%
 
03490622.6%
 
C2880712.1%
 
D2794782.1%
 
12433071.8%
 
H2289821.7%
 
F2177291.6%
 
22175651.6%
 
M1999221.5%
 
Y1810071.3%
 
U1751211.3%
 
K1645511.2%
 
G1636021.2%
 
-1622421.2%
 
Other values (52)12101999.0%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter708128252.4%
 
Lowercase Letter287156721.2%
 
Space Separator196697514.6%
 
Decimal Number13107949.7%
 
Dash Punctuation1622421.2%
 
Other Punctuation927920.7%
 
Open Punctuation142030.1%
 
Close Punctuation141490.1%
 
Connector Punctuation1912< 0.1%
 
Modifier Symbol118< 0.1%
 
Math Symbol51< 0.1%
 
Currency Symbol22< 0.1%
 
Other Symbol3< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
E76584010.8%
 
R6703309.5%
 
A5726198.1%
 
O4920486.9%
 
N4542136.4%
 
I4502346.4%
 
L4396486.2%
 
S3813035.4%
 
T3704955.2%
 
C2880714.1%
 
D2794783.9%
 
H2289823.2%
 
F2177293.1%
 
M1999222.8%
 
Y1810072.6%
 
U1751212.5%
 
K1645512.3%
 
G1636022.3%
 
P1574742.2%
 
B1546522.2%
 
W1503242.1%
 
V668770.9%
 
J243170.3%
 
Z148140.2%
 
X108030.2%
 
Other values (5)68280.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
1966975100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
#3103033.4%
 
.2873331.0%
 
/1532916.5%
 
,45684.9%
 
'43984.7%
 
&40714.4%
 
"32043.5%
 
@9151.0%
 
!1990.2%
 
*1320.1%
 
?1070.1%
 
\39< 0.1%
 
:34< 0.1%
 
;25< 0.1%
 
%7< 0.1%
 
¿1< 0.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
034906226.6%
 
124330718.6%
 
221756516.6%
 
31053908.0%
 
4876936.7%
 
5824876.3%
 
6607264.6%
 
7554074.2%
 
8550674.2%
 
9540904.1%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-162242100.0%
 

Most frequent Currency Symbol characters

ValueCountFrequency (%) 
$22100.0%
 

Most frequent Modifier Symbol characters

ValueCountFrequency (%) 
`11799.2%
 
^10.8%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_1912100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(1412499.4%
 
[610.4%
 
{180.1%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)1408599.5%
 
]590.4%
 
}5< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n191437866.7%
 
a95718933.3%
 

Most frequent Math Symbol characters

ValueCountFrequency (%) 
+3874.5%
 
=1019.6%
 
>23.9%
 
~12.0%
 

Most frequent Other Symbol characters

ValueCountFrequency (%) 
133.3%
 
133.3%
 
°133.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin995284973.6%
 
Common356326126.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n191437819.2%
 
a9571899.6%
 
E7658407.7%
 
R6703306.7%
 
A5726195.8%
 
O4920484.9%
 
N4542134.6%
 
I4502344.5%
 
L4396484.4%
 
S3813033.8%
 
T3704953.7%
 
C2880712.9%
 
D2794782.8%
 
H2289822.3%
 
F2177292.2%
 
M1999222.0%
 
Y1810071.8%
 
U1751211.8%
 
K1645511.7%
 
G1636021.6%
 
P1574741.6%
 
B1546521.6%
 
W1503241.5%
 
V668770.7%
 
J243170.2%
 
Other values (7)324450.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
196697555.2%
 
03490629.8%
 
12433076.8%
 
22175656.1%
 
-1622424.6%
 
31053903.0%
 
4876932.5%
 
5824872.3%
 
6607261.7%
 
7554071.6%
 
8550671.5%
 
9540901.5%
 
#310300.9%
 
.287330.8%
 
/153290.4%
 
(141240.4%
 
)140850.4%
 
,45680.1%
 
'43980.1%
 
&40710.1%
 
"32040.1%
 
_19120.1%
 
@915< 0.1%
 
!199< 0.1%
 
*132< 0.1%
 
Other values (20)550< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII13516086> 99.9%
 
None22< 0.1%
 
Box Drawing2< 0.1%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
196697514.6%
 
n191437814.2%
 
a9571897.1%
 
E7658405.7%
 
R6703305.0%
 
A5726194.2%
 
O4920483.6%
 
N4542133.4%
 
I4502343.3%
 
L4396483.3%
 
S3813032.8%
 
T3704952.7%
 
03490622.6%
 
C2880712.1%
 
D2794782.1%
 
12433071.8%
 
H2289821.7%
 
F2177291.6%
 
22175651.6%
 
M1999221.5%
 
Y1810071.3%
 
U1751211.3%
 
K1645511.2%
 
G1636021.2%
 
-1622421.2%
 
Other values (44)12101759.0%
 

Most frequent None characters

ValueCountFrequency (%) 
Ñ1777.3%
 
Æ14.5%
 
°14.5%
 
¿14.5%
 
É14.5%
 
À14.5%
 

Most frequent Box Drawing characters

ValueCountFrequency (%) 
150.0%
 
150.0%
 

ICS_209_INCIDENT_NUMBER
Categorical

HIGH CARDINALITY
MISSING

Distinct22737
Distinct (%)88.4%
Missing1854748
Missing (%)98.6%
Memory size14.3 MiB
OK-OSA-100020
 
53
MT-BRF-000135
 
46
WA-OWF-000583
 
41
CA-MNF-000663
 
39
ID-PAF-006068
 
39
Other values (22732)
25499 
ValueCountFrequency (%) 
OK-OSA-10002053< 0.1%
 
MT-BRF-00013546< 0.1%
 
WA-OWF-00058341< 0.1%
 
CA-MNF-00066339< 0.1%
 
ID-PAF-00606839< 0.1%
 
OR-UPF-00912137< 0.1%
 
WA-OLP-082035< 0.1%
 
OR-MHF-00001733< 0.1%
 
WA-OWF-00055932< 0.1%
 
ID-CWF-00001631< 0.1%
 
WA-MSF-0017730< 0.1%
 
CA-SHF-105729< 0.1%
 
CA-SRF-112029< 0.1%
 
OR-WSA-00010824< 0.1%
 
CA-PNF-132423< 0.1%
 
CA-MDF-00038823< 0.1%
 
OR-WSA-07323< 0.1%
 
AL-ALF-9901323< 0.1%
 
CA-MEU-00460822< 0.1%
 
OR-DEF-89321< 0.1%
 
CA-SHU-00472721< 0.1%
 
MT-FNF-03719< 0.1%
 
ID-BOF-00064219< 0.1%
 
CA-MNF-93416< 0.1%
 
WA-WEF-40615< 0.1%
 
Other values (22712)249941.3%
 
(Missing)185474898.6%
 
2020-11-18T18:04:21.366874image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique21712 ?
Unique (%)84.4%
2020-11-18T18:04:21.505852image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length19
Median length3
Mean length3.124264477
Min length3

Overview of Unicode Properties

Unique unicode characters59
Unique unicode categories11 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n370949663.1%
 
a185474831.6%
 
-497890.8%
 
0461820.8%
 
1196310.3%
 
2159740.3%
 
S142150.2%
 
F106830.2%
 
3104340.2%
 
A100570.2%
 
491720.2%
 
687440.1%
 
584650.1%
 
883550.1%
 
781250.1%
 
C78940.1%
 
978060.1%
 
N73370.1%
 
D66140.1%
 
T64990.1%
 
M63830.1%
 
O62600.1%
 
K54130.1%
 
L48170.1%
 
R38090.1%
 
Other values (34)281680.5%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter556426294.7%
 
Decimal Number1428882.4%
 
Uppercase Letter1170272.0%
 
Dash Punctuation497890.8%
 
Space Separator1076< 0.1%
 
Other Punctuation17< 0.1%
 
Connector Punctuation7< 0.1%
 
Modifier Symbol1< 0.1%
 
Currency Symbol1< 0.1%
 
Open Punctuation1< 0.1%
 
Close Punctuation1< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n370949666.7%
 
a185474833.3%
 
p5< 0.1%
 
y3< 0.1%
 
f2< 0.1%
 
k2< 0.1%
 
r2< 0.1%
 
s2< 0.1%
 
c1< 0.1%
 
h1< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
S1421512.1%
 
F106839.1%
 
A100578.6%
 
C78946.7%
 
N73376.3%
 
D66145.7%
 
T64995.6%
 
M63835.5%
 
O62605.3%
 
K54134.6%
 
L48174.1%
 
R38093.3%
 
W37413.2%
 
I32402.8%
 
U31712.7%
 
X31422.7%
 
V24192.1%
 
P23152.0%
 
Y21741.9%
 
E18621.6%
 
B18201.6%
 
Z10640.9%
 
G9050.8%
 
H8180.7%
 
J2280.2%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-49789100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
04618232.3%
 
11963113.7%
 
21597411.2%
 
3104347.3%
 
491726.4%
 
687446.1%
 
584655.9%
 
883555.8%
 
781255.7%
 
978065.5%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/741.2%
 
.635.3%
 
?15.9%
 
!15.9%
 
#15.9%
 
:15.9%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
1076100.0%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_7100.0%
 

Most frequent Modifier Symbol characters

ValueCountFrequency (%) 
`1100.0%
 

Most frequent Currency Symbol characters

ValueCountFrequency (%) 
$1100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(1100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)1100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin568128996.7%
 
Common1937813.3%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n370949665.3%
 
a185474832.6%
 
S142150.3%
 
F106830.2%
 
A100570.2%
 
C78940.1%
 
N73370.1%
 
D66140.1%
 
T64990.1%
 
M63830.1%
 
O62600.1%
 
K54130.1%
 
L48170.1%
 
R38090.1%
 
W37410.1%
 
I32400.1%
 
U31710.1%
 
X31420.1%
 
V2419< 0.1%
 
P2315< 0.1%
 
Y2174< 0.1%
 
E1862< 0.1%
 
B1820< 0.1%
 
Z1064< 0.1%
 
G905< 0.1%
 
Other values (11)1211< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
-4978925.7%
 
04618223.8%
 
11963110.1%
 
2159748.2%
 
3104345.4%
 
491724.7%
 
687444.5%
 
584654.4%
 
883554.3%
 
781254.2%
 
978064.0%
 
10760.6%
 
_7< 0.1%
 
/7< 0.1%
 
.6< 0.1%
 
?1< 0.1%
 
!1< 0.1%
 
#1< 0.1%
 
`1< 0.1%
 
$1< 0.1%
 
(1< 0.1%
 
)1< 0.1%
 
:1< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII5875070100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n370949663.1%
 
a185474831.6%
 
-497890.8%
 
0461820.8%
 
1196310.3%
 
2159740.3%
 
S142150.2%
 
F106830.2%
 
3104340.2%
 
A100570.2%
 
491720.2%
 
687440.1%
 
584650.1%
 
883550.1%
 
781250.1%
 
C78940.1%
 
978060.1%
 
N73370.1%
 
D66140.1%
 
T64990.1%
 
M63830.1%
 
O62600.1%
 
K54130.1%
 
L48170.1%
 
R38090.1%
 
Other values (34)281680.5%
 

ICS_209_NAME
Categorical

HIGH CARDINALITY
MISSING

Distinct19573
Distinct (%)76.1%
Missing1854748
Missing (%)98.6%
Memory size14.3 MiB
OSAGE-MIAMI COMPLEX
 
53
Selway-Salmon WFU Complex
 
46
YAKIMA COMPLEX
 
41
South Fork Complex
 
39
Yolla Bolly Complex
 
39
Other values (19568)
25499 
ValueCountFrequency (%) 
OSAGE-MIAMI COMPLEX53< 0.1%
 
Selway-Salmon WFU Complex46< 0.1%
 
YAKIMA COMPLEX41< 0.1%
 
South Fork Complex39< 0.1%
 
Yolla Bolly Complex39< 0.1%
 
Tiller Complex37< 0.1%
 
Olympic Complex35< 0.1%
 
Clackamas River Complex33< 0.1%
 
Wenatchee Complex32< 0.1%
 
Middle Fork Complex31< 0.1%
 
Clear/Nez Complex31< 0.1%
 
Gold Hill Complex30< 0.1%
 
Mad Complex29< 0.1%
 
Iron & Alps Complexes29< 0.1%
 
HOUGH COMPLEX23< 0.1%
 
Bankhead Complex23< 0.1%
 
High Cascades23< 0.1%
 
Muldoon Complex23< 0.1%
 
Summit Springs Complex23< 0.1%
 
WSA Lightning Complex23< 0.1%
 
MEU Lightning Complex22< 0.1%
 
SHU LIGHTNING COMPLEX21< 0.1%
 
COTTONWOOD20< 0.1%
 
Ltl Salmon CK Fire Use Complex19< 0.1%
 
Lake Complex17< 0.1%
 
Other values (19548)249751.3%
 
(Missing)185474898.6%
 
2020-11-18T18:04:21.712850image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique17035 ?
Unique (%)66.2%
2020-11-18T18:04:21.871871image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length37
Median length3
Mean length3.108786922
Min length2

Overview of Unicode Properties

Unique unicode characters79
Unique unicode categories10 ?
Unique unicode scripts2 ?
Unique unicode blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n371906163.6%
 
a186675131.9%
 
225120.4%
 
e200020.3%
 
o127950.2%
 
r119250.2%
 
l104450.2%
 
C102300.2%
 
i101500.2%
 
E100420.2%
 
R94700.2%
 
t70140.1%
 
L70140.1%
 
A69620.1%
 
O68340.1%
 
S64090.1%
 
I53930.1%
 
N53380.1%
 
T49620.1%
 
M49440.1%
 
s49350.1%
 
F46350.1%
 
d44430.1%
 
B43530.1%
 
H43230.1%
 
Other values (54)650231.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter570352897.6%
 
Uppercase Letter1136401.9%
 
Space Separator225130.4%
 
Decimal Number45200.1%
 
Other Punctuation1066< 0.1%
 
Dash Punctuation533< 0.1%
 
Open Punctuation81< 0.1%
 
Close Punctuation81< 0.1%
 
Connector Punctuation2< 0.1%
 
Math Symbol1< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n371906165.2%
 
a186675132.7%
 
e200020.4%
 
o127950.2%
 
r119250.2%
 
l104450.2%
 
i101500.2%
 
t70140.1%
 
s49350.1%
 
d44430.1%
 
k43190.1%
 
m42710.1%
 
p40670.1%
 
u37720.1%
 
h36450.1%
 
c30280.1%
 
y2797< 0.1%
 
g2692< 0.1%
 
x2427< 0.1%
 
w1777< 0.1%
 
v1077< 0.1%
 
b1031< 0.1%
 
f740< 0.1%
 
z244< 0.1%
 
q82< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
C102309.0%
 
E100428.8%
 
R94708.3%
 
L70146.2%
 
A69626.1%
 
O68346.0%
 
S64095.6%
 
I53934.7%
 
N53384.7%
 
T49624.4%
 
M49444.4%
 
F46354.1%
 
B43533.8%
 
H43233.8%
 
P39373.5%
 
D34753.1%
 
W29992.6%
 
K27492.4%
 
G27152.4%
 
U25372.2%
 
Y16591.5%
 
X8980.8%
 
V8640.8%
 
J6370.6%
 
Z1360.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
22512> 99.9%
 
 1< 0.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
296621.4%
 
185218.8%
 
053811.9%
 
347110.4%
 
43688.1%
 
53317.3%
 
72685.9%
 
62615.8%
 
82365.2%
 
92295.1%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-533100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.36133.9%
 
#31829.8%
 
'17316.2%
 
/15014.1%
 
&504.7%
 
,60.6%
 
@40.4%
 
"20.2%
 
\10.1%
 
*10.1%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(81100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)81100.0%
 

Most frequent Math Symbol characters

ValueCountFrequency (%) 
=1100.0%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_2100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin581716899.5%
 
Common287970.5%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n371906163.9%
 
a186675132.1%
 
e200020.3%
 
o127950.2%
 
r119250.2%
 
l104450.2%
 
C102300.2%
 
i101500.2%
 
E100420.2%
 
R94700.2%
 
t70140.1%
 
L70140.1%
 
A69620.1%
 
O68340.1%
 
S64090.1%
 
I53930.1%
 
N53380.1%
 
T49620.1%
 
M49440.1%
 
s49350.1%
 
F46350.1%
 
d44430.1%
 
B43530.1%
 
H43230.1%
 
k43190.1%
 
Other values (27)544190.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
2251278.2%
 
29663.4%
 
18523.0%
 
05381.9%
 
-5331.9%
 
34711.6%
 
43681.3%
 
.3611.3%
 
53311.1%
 
#3181.1%
 
72680.9%
 
62610.9%
 
82360.8%
 
92290.8%
 
'1730.6%
 
/1500.5%
 
(810.3%
 
)810.3%
 
&500.2%
 
,6< 0.1%
 
@4< 0.1%
 
"2< 0.1%
 
_2< 0.1%
 
 1< 0.1%
 
\1< 0.1%
 
Other values (2)2< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII5845964> 99.9%
 
None1< 0.1%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n371906163.6%
 
a186675131.9%
 
225120.4%
 
e200020.3%
 
o127950.2%
 
r119250.2%
 
l104450.2%
 
C102300.2%
 
i101500.2%
 
E100420.2%
 
R94700.2%
 
t70140.1%
 
L70140.1%
 
A69620.1%
 
O68340.1%
 
S64090.1%
 
I53930.1%
 
N53380.1%
 
T49620.1%
 
M49440.1%
 
s49350.1%
 
F46350.1%
 
d44430.1%
 
B43530.1%
 
H43230.1%
 
Other values (53)650221.1%
 

Most frequent None characters

ValueCountFrequency (%) 
 1100.0%
 

MTBS_ID
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct10481
Distinct (%)95.3%
Missing1869462
Missing (%)99.4%
Memory size14.3 MiB
KY3686008359020011102
 
12
ID4542411459020120730
 
9
ID4568011472320070706
 
8
MT4574610716620120731
 
7
OR4493112043020110824
 
7
Other values (10476)
10960 
ValueCountFrequency (%) 
KY368600835902001110212< 0.1%
 
ID45424114590201207309< 0.1%
 
ID45680114723200707068< 0.1%
 
MT45746107166201207317< 0.1%
 
OR44931120430201108247< 0.1%
 
UT39789112292199608026< 0.1%
 
NV40116117067200707166< 0.1%
 
CA39852121444200808146< 0.1%
 
KY37860082988200111025< 0.1%
 
ID45056114891200007315< 0.1%
 
TX32097101167201102275< 0.1%
 
ID45105115708200707065< 0.1%
 
CA40546122663200806215< 0.1%
 
ID44750115548200707175< 0.1%
 
NV37242114303200506225< 0.1%
 
MT47693115217201408045< 0.1%
 
OR43822119389200707065< 0.1%
 
WA48230118702201408044< 0.1%
 
TN36106084384200111074< 0.1%
 
MN48038095444200304094< 0.1%
 
CA39722121191200806214< 0.1%
 
KY37423083225200111014< 0.1%
 
ID45216115521199408114< 0.1%
 
ID42160115321200707214< 0.1%
 
CA41614123658200806214< 0.1%
 
Other values (10456)108650.6%
 
(Missing)186946299.4%
 
2020-11-18T18:04:22.047880image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique10136 ?
Unique (%)92.1%
2020-11-18T18:04:22.173883image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length29
Median length3
Mean length3.105630256
Min length3

Overview of Unicode Properties

Unique unicode characters39
Unique unicode categories4 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n373892464.0%
 
a186946232.0%
 
0430780.7%
 
1340680.6%
 
2249840.4%
 
9171320.3%
 
3169880.3%
 
4166900.3%
 
8139370.2%
 
6138260.2%
 
5128330.2%
 
7127160.2%
 
A35060.1%
 
N1939< 0.1%
 
T1921< 0.1%
 
M1631< 0.1%
 
K1571< 0.1%
 
C1513< 0.1%
 
D1410< 0.1%
 
-1398< 0.1%
 
O1348< 0.1%
 
I1209< 0.1%
 
V994< 0.1%
 
W932< 0.1%
 
R823< 0.1%
 
Other values (14)51960.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter560838696.0%
 
Decimal Number2062523.5%
 
Uppercase Letter239930.4%
 
Dash Punctuation1398< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n373892466.7%
 
a186946233.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
A350614.6%
 
N19398.1%
 
T19218.0%
 
M16316.8%
 
K15716.5%
 
C15136.3%
 
D14105.9%
 
O13485.6%
 
I12095.0%
 
V9944.1%
 
W9323.9%
 
R8233.4%
 
S7553.1%
 
L7433.1%
 
X7193.0%
 
F6522.7%
 
Z5602.3%
 
U5192.2%
 
Y5042.1%
 
P2230.9%
 
E1680.7%
 
B1530.6%
 
G1170.5%
 
J370.2%
 
H360.2%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
04307820.9%
 
13406816.5%
 
22498412.1%
 
9171328.3%
 
3169888.2%
 
4166908.1%
 
8139376.8%
 
6138266.7%
 
5128336.2%
 
7127166.2%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-1398100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin563237996.4%
 
Common2076503.6%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n373892466.4%
 
a186946233.2%
 
A35060.1%
 
N1939< 0.1%
 
T1921< 0.1%
 
M1631< 0.1%
 
K1571< 0.1%
 
C1513< 0.1%
 
D1410< 0.1%
 
O1348< 0.1%
 
I1209< 0.1%
 
V994< 0.1%
 
W932< 0.1%
 
R823< 0.1%
 
S755< 0.1%
 
L743< 0.1%
 
X719< 0.1%
 
F652< 0.1%
 
Z560< 0.1%
 
U519< 0.1%
 
Y504< 0.1%
 
P223< 0.1%
 
E168< 0.1%
 
B153< 0.1%
 
G117< 0.1%
 
Other values (3)83< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
04307820.7%
 
13406816.4%
 
22498412.0%
 
9171328.3%
 
3169888.2%
 
4166908.0%
 
8139376.7%
 
6138266.7%
 
5128336.2%
 
7127166.1%
 
-13980.7%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII5840029100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n373892464.0%
 
a186946232.0%
 
0430780.7%
 
1340680.6%
 
2249840.4%
 
9171320.3%
 
3169880.3%
 
4166900.3%
 
8139370.2%
 
6138260.2%
 
5128330.2%
 
7127160.2%
 
A35060.1%
 
N1939< 0.1%
 
T1921< 0.1%
 
M1631< 0.1%
 
K1571< 0.1%
 
C1513< 0.1%
 
D1410< 0.1%
 
-1398< 0.1%
 
O1348< 0.1%
 
I1209< 0.1%
 
V994< 0.1%
 
W932< 0.1%
 
R823< 0.1%
 
Other values (14)51960.1%
 

MTBS_FIRE_NAME
Categorical

HIGH CARDINALITY
MISSING

Distinct8133
Distinct (%)73.9%
Missing1869462
Missing (%)99.4%
Memory size14.3 MiB
UNNAMED
 
752
COTTONWOOD
 
24
CANYON
 
14
BEAR
 
12
WILLOW
 
12
Other values (8128)
10189 
ValueCountFrequency (%) 
UNNAMED752< 0.1%
 
COTTONWOOD24< 0.1%
 
CANYON14< 0.1%
 
BEAR12< 0.1%
 
WILLOW12< 0.1%
 
BEAR CREEK12< 0.1%
 
COYOTE12< 0.1%
 
SHEEP11< 0.1%
 
WILLOW CREEK11< 0.1%
 
SPRING10< 0.1%
 
ANTELOPE10< 0.1%
 
MUSTANG10< 0.1%
 
RATTLESNAKE10< 0.1%
 
MUSTANG COMPLEX9< 0.1%
 
PINE9< 0.1%
 
WILDCAT9< 0.1%
 
CAMP CREEK9< 0.1%
 
COUNTY LINE9< 0.1%
 
WALKER9< 0.1%
 
BIG CREEK9< 0.1%
 
BUCKSKIN9< 0.1%
 
BITTERROOT FIRE USE COMPLEX (MAGRUDER MTN #1)8< 0.1%
 
WINDMILL8< 0.1%
 
CLOVER8< 0.1%
 
ROCKY8< 0.1%
 
Other values (8108)99990.5%
 
(Missing)186946299.4%
 
2020-11-18T18:04:22.330875image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique6975 ?
Unique (%)63.4%
2020-11-18T18:04:22.473874image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length49
Median length3
Mean length3.044267774
Min length2

Overview of Unicode Properties

Unique unicode characters49
Unique unicode categories8 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n373892765.3%
 
a186946532.7%
 
E121730.2%
 
A84230.1%
 
R79020.1%
 
N78120.1%
 
78040.1%
 
O76280.1%
 
L67710.1%
 
I59100.1%
 
C52430.1%
 
T50940.1%
 
S46920.1%
 
M42280.1%
 
D37620.1%
 
U34450.1%
 
P31370.1%
 
H31220.1%
 
K31150.1%
 
B2326< 0.1%
 
G2219< 0.1%
 
W1947< 0.1%
 
Y1812< 0.1%
 
F1523< 0.1%
 
X1146< 0.1%
 
Other values (24)50130.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter560839598.0%
 
Uppercase Letter1048891.8%
 
Space Separator78040.1%
 
Decimal Number1822< 0.1%
 
Open Punctuation620< 0.1%
 
Close Punctuation620< 0.1%
 
Other Punctuation299< 0.1%
 
Dash Punctuation190< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n373892766.7%
 
a186946533.3%
 
d3< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
E1217311.6%
 
A84238.0%
 
R79027.5%
 
N78127.4%
 
O76287.3%
 
L67716.5%
 
I59105.6%
 
C52435.0%
 
T50944.9%
 
S46924.5%
 
M42284.0%
 
D37623.6%
 
U34453.3%
 
P31373.0%
 
H31223.0%
 
K31153.0%
 
B23262.2%
 
G22192.1%
 
W19471.9%
 
Y18121.7%
 
F15231.5%
 
X11461.1%
 
V8470.8%
 
J3140.3%
 
Z2140.2%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
7804100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(620100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)620100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
245224.8%
 
130816.9%
 
322212.2%
 
019110.5%
 
41488.1%
 
51307.1%
 
61055.8%
 
7985.4%
 
8904.9%
 
9784.3%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-190100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
#11538.5%
 
.9331.1%
 
'4414.7%
 
/3110.4%
 
&144.7%
 
"20.7%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin571328499.8%
 
Common113550.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n373892765.4%
 
a186946532.7%
 
E121730.2%
 
A84230.1%
 
R79020.1%
 
N78120.1%
 
O76280.1%
 
L67710.1%
 
I59100.1%
 
C52430.1%
 
T50940.1%
 
S46920.1%
 
M42280.1%
 
D37620.1%
 
U34450.1%
 
P31370.1%
 
H31220.1%
 
K31150.1%
 
B2326< 0.1%
 
G2219< 0.1%
 
W1947< 0.1%
 
Y1812< 0.1%
 
F1523< 0.1%
 
X1146< 0.1%
 
V847< 0.1%
 
Other values (4)615< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
780468.7%
 
(6205.5%
 
)6205.5%
 
24524.0%
 
13082.7%
 
32222.0%
 
01911.7%
 
-1901.7%
 
41481.3%
 
51301.1%
 
#1151.0%
 
61050.9%
 
7980.9%
 
.930.8%
 
8900.8%
 
9780.7%
 
'440.4%
 
/310.3%
 
&140.1%
 
"2< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII5724639100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n373892765.3%
 
a186946532.7%
 
E121730.2%
 
A84230.1%
 
R79020.1%
 
N78120.1%
 
78040.1%
 
O76280.1%
 
L67710.1%
 
I59100.1%
 
C52430.1%
 
T50940.1%
 
S46920.1%
 
M42280.1%
 
D37620.1%
 
U34450.1%
 
P31370.1%
 
H31220.1%
 
K31150.1%
 
B2326< 0.1%
 
G2219< 0.1%
 
W1947< 0.1%
 
Y1812< 0.1%
 
F1523< 0.1%
 
X1146< 0.1%
 
Other values (24)50130.1%
 

COMPLEX_NAME
Categorical

HIGH CARDINALITY
MISSING

Distinct1416
Distinct (%)27.3%
Missing1875282
Missing (%)99.7%
Memory size14.3 MiB
OSAGE-MIAMI COMPLEX
 
54
TILLER COMPLEX
 
50
MOTORWAY COMPLEX
 
49
SELWAY-SALMON WFU COMPLEX
 
46
SOUTH FORK COMPLEX
 
42
Other values (1411)
4942 
ValueCountFrequency (%) 
OSAGE-MIAMI COMPLEX54< 0.1%
 
TILLER COMPLEX50< 0.1%
 
MOTORWAY COMPLEX49< 0.1%
 
SELWAY-SALMON WFU COMPLEX46< 0.1%
 
SOUTH FORK COMPLEX42< 0.1%
 
YAKIMA COMPLEX41< 0.1%
 
YOLLA BOLLY COMPLEX 200839< 0.1%
 
CLEAR/NEZ COMPLEX38< 0.1%
 
VALLEY COMPLEX37< 0.1%
 
OLYMPIC COMPLEX36< 0.1%
 
WENATCHEE RIVER COMPLEX34< 0.1%
 
CLACKAMAS RIVER COMPLEX33< 0.1%
 
MIDDLE FORK COMPLEX31< 0.1%
 
IRON & ALPS COMPLEXES30< 0.1%
 
GOLD HILL COMPLEX30< 0.1%
 
MAD COMPLEX29< 0.1%
 
ELK CITY COMPLEX28< 0.1%
 
POWELL SBW COMPLEX28< 0.1%
 
SOUTHEAST TEXAS FIRE COMPLEX24< 0.1%
 
MOOSE CREEK WFU COMPLEX24< 0.1%
 
WILDERNESS COMPLEX23< 0.1%
 
BANKHEAD COMPLEX23< 0.1%
 
HIGH CASCADES COMPLEX23< 0.1%
 
MULDOON COMPLEX23< 0.1%
 
HOUGH COMPLEX23< 0.1%
 
Other values (1391)43450.2%
 
(Missing)187528299.7%
 
2020-11-18T18:04:22.631849image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique612 ?
Unique (%)11.8%
2020-11-18T18:04:22.769851image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length43
Median length3
Mean length3.040111887
Min length3

Overview of Unicode Properties

Unique unicode characters49
Unique unicode categories8 ?
Unique unicode scripts2 ?
Unique unicode blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n375056465.6%
 
a187528232.8%
 
E100720.2%
 
O83400.1%
 
L83400.1%
 
80570.1%
 
C68730.1%
 
M66020.1%
 
P60080.1%
 
X52140.1%
 
A39110.1%
 
R34750.1%
 
I29170.1%
 
N2829< 0.1%
 
T2502< 0.1%
 
S2477< 0.1%
 
H1665< 0.1%
 
U1529< 0.1%
 
K1410< 0.1%
 
D1402< 0.1%
 
G1194< 0.1%
 
Y1091< 0.1%
 
W1022< 0.1%
 
B977< 0.1%
 
F665< 0.1%
 
Other values (24)2406< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter562584698.4%
 
Uppercase Letter812861.4%
 
Space Separator82120.1%
 
Decimal Number956< 0.1%
 
Dash Punctuation239< 0.1%
 
Other Punctuation239< 0.1%
 
Open Punctuation23< 0.1%
 
Close Punctuation23< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n375056466.7%
 
a187528233.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
E1007212.4%
 
O834010.3%
 
L834010.3%
 
C68738.5%
 
M66028.1%
 
P60087.4%
 
X52146.4%
 
A39114.8%
 
R34754.3%
 
I29173.6%
 
N28293.5%
 
T25023.1%
 
S24773.0%
 
H16652.0%
 
U15291.9%
 
K14101.7%
 
D14021.7%
 
G11941.5%
 
Y10911.3%
 
W10221.3%
 
B9771.2%
 
F6650.8%
 
V4780.6%
 
Z1760.2%
 
J800.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
805798.1%
 
 1551.9%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
029931.3%
 
219019.9%
 
8858.9%
 
1677.0%
 
7626.5%
 
3596.2%
 
5555.8%
 
4555.8%
 
9505.2%
 
6343.6%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-239100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/12251.0%
 
.4719.7%
 
&3615.1%
 
'2410.0%
 
#83.3%
 
"20.8%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(23100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)23100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin570713299.8%
 
Common96920.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n375056465.7%
 
a187528232.9%
 
E100720.2%
 
O83400.1%
 
L83400.1%
 
C68730.1%
 
M66020.1%
 
P60080.1%
 
X52140.1%
 
A39110.1%
 
R34750.1%
 
I29170.1%
 
N2829< 0.1%
 
T2502< 0.1%
 
S2477< 0.1%
 
H1665< 0.1%
 
U1529< 0.1%
 
K1410< 0.1%
 
D1402< 0.1%
 
G1194< 0.1%
 
Y1091< 0.1%
 
W1022< 0.1%
 
B977< 0.1%
 
F665< 0.1%
 
V478< 0.1%
 
Other values (3)293< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
805783.1%
 
02993.1%
 
-2392.5%
 
21902.0%
 
 1551.6%
 
/1221.3%
 
8850.9%
 
1670.7%
 
7620.6%
 
3590.6%
 
5550.6%
 
4550.6%
 
9500.5%
 
.470.5%
 
&360.4%
 
6340.4%
 
'240.2%
 
(230.2%
 
)230.2%
 
#80.1%
 
"2< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII5716669> 99.9%
 
None155< 0.1%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n375056465.6%
 
a187528232.8%
 
E100720.2%
 
O83400.1%
 
L83400.1%
 
80570.1%
 
C68730.1%
 
M66020.1%
 
P60080.1%
 
X52140.1%
 
A39110.1%
 
R34750.1%
 
I29170.1%
 
N2829< 0.1%
 
T2502< 0.1%
 
S2477< 0.1%
 
H1665< 0.1%
 
U1529< 0.1%
 
K1410< 0.1%
 
D1402< 0.1%
 
G1194< 0.1%
 
Y1091< 0.1%
 
W1022< 0.1%
 
B977< 0.1%
 
F665< 0.1%
 
Other values (23)2251< 0.1%
 

Most frequent None characters

ValueCountFrequency (%) 
 155100.0%
 

FIRE_YEAR
Real number (ℝ≥0)

HIGH CORRELATION

Distinct24
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2003.709974
Minimum1992
Maximum2015
Zeros0
Zeros (%)0.0%
Memory size14.3 MiB
2020-11-18T18:04:22.878874image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1992
5-th percentile1993
Q11998
median2004
Q32009
95-th percentile2014
Maximum2015
Range23
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.663098594
Coefficient of variation (CV)0.003325380758
Kurtosis-1.113110996
Mean2003.709974
Median Absolute Deviation (MAD)5
Skewness-0.05698186052
Sum3767906477
Variance44.39688288
MonotocityNot monotonic
2020-11-18T18:04:22.974874image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%) 
20061140046.1%
 
2000964165.1%
 
2007955735.1%
 
2011905524.8%
 
1999893634.8%
 
2005886044.7%
 
2001865874.6%
 
2008853784.5%
 
2010798894.2%
 
2009783254.2%
 
1994759554.0%
 
2002756564.0%
 
1996755744.0%
 
2015744914.0%
 
2012727693.9%
 
1995714723.8%
 
2004692793.7%
 
1998683703.6%
 
2003682613.6%
 
1992679753.6%
 
2014677533.6%
 
2013647803.4%
 
1993619893.3%
 
1997614503.3%
 
ValueCountFrequency (%) 
1992679753.6%
 
1993619893.3%
 
1994759554.0%
 
1995714723.8%
 
1996755744.0%
 
1997614503.3%
 
1998683703.6%
 
1999893634.8%
 
2000964165.1%
 
2001865874.6%
 
ValueCountFrequency (%) 
2015744914.0%
 
2014677533.6%
 
2013647803.4%
 
2012727693.9%
 
2011905524.8%
 
2010798894.2%
 
2009783254.2%
 
2008853784.5%
 
2007955735.1%
 
20061140046.1%
 

DISCOVERY_DATE
Real number (ℝ≥0)

HIGH CORRELATION

Distinct8766
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2453063.657
Minimum2448622.5
Maximum2457387.5
Zeros0
Zeros (%)0.0%
Memory size14.3 MiB
2020-11-18T18:04:23.097874image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum2448622.5
5-th percentile2449148.5
Q12451084.5
median2453177.5
Q32455035.5
95-th percentile2456867.5
Maximum2457387.5
Range8765
Interquartile range (IQR)3951

Descriptive statistics

Standard deviation2434.573159
Coefficient of variation (CV)0.0009924622837
Kurtosis-1.105805095
Mean2453063.657
Median Absolute Deviation (MAD)1963
Skewness-0.05760334535
Sum4.61290035e+12
Variance5927146.467
MonotocityNot monotonic
2020-11-18T18:04:23.251851image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
2454506.512080.1%
 
2453441.511770.1%
 
2453798.511210.1%
 
2455611.511080.1%
 
2449430.510700.1%
 
2453799.510520.1%
 
2453476.510010.1%
 
2456112.59580.1%
 
2454575.5936< 0.1%
 
2449773.5933< 0.1%
 
2449056.5927< 0.1%
 
2449801.5920< 0.1%
 
2448683.5917< 0.1%
 
2451610.5912< 0.1%
 
2450137.5911< 0.1%
 
2453077.5907< 0.1%
 
2453477.5898< 0.1%
 
2453802.5886< 0.1%
 
2453920.5876< 0.1%
 
2450165.5873< 0.1%
 
2450138.5872< 0.1%
 
2452323.5865< 0.1%
 
2454638.5862< 0.1%
 
2451257.5853< 0.1%
 
2453840.5849< 0.1%
 
Other values (8741)185657398.7%
 
ValueCountFrequency (%) 
2448622.5129< 0.1%
 
2448623.546< 0.1%
 
2448624.543< 0.1%
 
2448625.568< 0.1%
 
2448626.544< 0.1%
 
2448627.592< 0.1%
 
2448628.5152< 0.1%
 
2448629.585< 0.1%
 
2448630.535< 0.1%
 
2448631.572< 0.1%
 
ValueCountFrequency (%) 
2457387.522< 0.1%
 
2457386.517< 0.1%
 
2457385.526< 0.1%
 
2457384.520< 0.1%
 
2457383.511< 0.1%
 
2457382.533< 0.1%
 
2457381.519< 0.1%
 
2457380.537< 0.1%
 
2457379.534< 0.1%
 
2457378.546< 0.1%
 

DISCOVERY_DOY
Real number (ℝ≥0)

HIGH CORRELATION

Distinct366
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean164.719145
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Memory size14.3 MiB
2020-11-18T18:04:23.408852image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile31
Q189
median164
Q3230
95-th percentile322
Maximum366
Range365
Interquartile range (IQR)141

Descriptive statistics

Standard deviation90.03890916
Coefficient of variation (CV)0.54662079
Kurtosis-0.8901164788
Mean164.719145
Median Absolute Deviation (MAD)71
Skewness0.2241694798
Sum309748587
Variance8107.005164
MonotocityNot monotonic
2020-11-18T18:04:23.875848image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
185128750.7%
 
186115350.6%
 
10192610.5%
 
6792600.5%
 
10892560.5%
 
10092480.5%
 
8389490.5%
 
9589240.5%
 
10988500.5%
 
10787870.5%
 
9287760.5%
 
18486360.5%
 
7086270.5%
 
8285830.5%
 
7485470.5%
 
18785150.5%
 
9684940.5%
 
7384760.5%
 
8484580.4%
 
10284400.4%
 
9984230.4%
 
10683110.4%
 
9782690.4%
 
10382630.4%
 
10482080.4%
 
Other values (341)165649488.1%
 
ValueCountFrequency (%) 
139710.2%
 
227190.1%
 
325060.1%
 
424490.1%
 
527030.1%
 
625710.1%
 
728740.2%
 
829080.2%
 
923940.1%
 
1023540.1%
 
ValueCountFrequency (%) 
366544< 0.1%
 
36527330.1%
 
36421440.1%
 
36321760.1%
 
36224200.1%
 
36125140.1%
 
36019820.1%
 
35912900.1%
 
35815260.1%
 
35717940.1%
 

DISCOVERY_TIME
Categorical

HIGH CARDINALITY
MISSING

Distinct1440
Distinct (%)0.1%
Missing882638
Missing (%)46.9%
Memory size14.3 MiB
1400
 
20981
1500
 
20020
1600
 
18234
1300
 
17280
1700
 
14027
Other values (1435)
907285 
ValueCountFrequency (%) 
1400209811.1%
 
1500200201.1%
 
1600182341.0%
 
1300172800.9%
 
1700140270.7%
 
1200139630.7%
 
1530129930.7%
 
1430129010.7%
 
1800120120.6%
 
1630115540.6%
 
1330113080.6%
 
110092650.5%
 
173087850.5%
 
100086880.5%
 
123086840.5%
 
190083320.4%
 
200068590.4%
 
183066170.4%
 
113063770.3%
 
151561810.3%
 
141561760.3%
 
144559970.3%
 
080059650.3%
 
090057590.3%
 
154557000.3%
 
Other values (1415)73316939.0%
 
(Missing)88263846.9%
 
2020-11-18T18:04:24.125850image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-18T18:04:24.291768image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length4
Mean length3.530627797
Min length3

Overview of Unicode Properties

Unique unicode characters12
Unique unicode categories2 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n176527626.6%
 
1109454816.5%
 
a88263813.3%
 
086720913.1%
 
54203376.3%
 
33731025.6%
 
23612695.4%
 
43195754.8%
 
61623512.4%
 
71418522.1%
 
81351892.0%
 
91158761.7%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number399130860.1%
 
Lowercase Letter264791439.9%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
1109454827.4%
 
086720921.7%
 
542033710.5%
 
33731029.3%
 
23612699.1%
 
43195758.0%
 
61623514.1%
 
71418523.6%
 
81351893.4%
 
91158762.9%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n176527666.7%
 
a88263833.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common399130860.1%
 
Latin264791439.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
1109454827.4%
 
086720921.7%
 
542033710.5%
 
33731029.3%
 
23612699.1%
 
43195758.0%
 
61623514.1%
 
71418523.6%
 
81351893.4%
 
91158762.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n176527666.7%
 
a88263833.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII6639222100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n176527626.6%
 
1109454816.5%
 
a88263813.3%
 
086720913.1%
 
54203376.3%
 
33731025.6%
 
23612695.4%
 
43195754.8%
 
61623512.4%
 
71418522.1%
 
81351892.0%
 
91158761.7%
 

STAT_CAUSE_CODE
Real number (ℝ≥0)

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.9790371
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Memory size14.3 MiB
2020-11-18T18:04:24.422740image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q39
95-th percentile13
Maximum13
Range12
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.483860199
Coefficient of variation (CV)0.5826791406
Kurtosis-0.6013728157
Mean5.9790371
Median Absolute Deviation (MAD)3
Skewness0.3115850498
Sum11243370
Variance12.13728188
MonotocityNot monotonic
2020-11-18T18:04:24.552741image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%) 
542902822.8%
 
932380517.2%
 
728145515.0%
 
127846814.8%
 
131667238.9%
 
21476127.8%
 
4761394.0%
 
8611673.3%
 
3528692.8%
 
6334551.8%
 
11144480.8%
 
10115000.6%
 
1237960.2%
 
ValueCountFrequency (%) 
127846814.8%
 
21476127.8%
 
3528692.8%
 
4761394.0%
 
542902822.8%
 
6334551.8%
 
728145515.0%
 
8611673.3%
 
932380517.2%
 
10115000.6%
 
ValueCountFrequency (%) 
131667238.9%
 
1237960.2%
 
11144480.8%
 
10115000.6%
 
932380517.2%
 
8611673.3%
 
728145515.0%
 
6334551.8%
 
542902822.8%
 
4761394.0%
 

STAT_CAUSE_DESCR
Categorical

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size14.3 MiB
Debris Burning
429028 
Miscellaneous
323805 
Arson
281455 
Lightning
278468 
Missing/Undefined
166723 
Other values (8)
400986 
ValueCountFrequency (%) 
Debris Burning42902822.8%
 
Miscellaneous32380517.2%
 
Arson28145515.0%
 
Lightning27846814.8%
 
Missing/Undefined1667238.9%
 
Equipment Use1476127.8%
 
Campfire761394.0%
 
Children611673.3%
 
Smoking528692.8%
 
Railroad334551.8%
 
Powerline144480.8%
 
Fireworks115000.6%
 
Structure37960.2%
 
2020-11-18T18:04:24.704740image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-18T18:04:24.822773image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length17
Median length13
Mean length11.10707086
Min length5

Overview of Unicode Properties

Unique unicode characters35
Unique unicode categories4 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n279651713.4%
 
i263615612.6%
 
e18868069.0%
 
s18506518.9%
 
r13553126.5%
 
g12055565.8%
 
u9080374.3%
 
l7566803.6%
 
o7175323.4%
 
5766402.8%
 
M4905282.3%
 
a4668542.2%
 
t4336722.1%
 
D4290282.1%
 
b4290282.1%
 
B4290282.1%
 
d4280682.0%
 
h3396351.6%
 
c3276011.6%
 
U3143351.5%
 
A2814551.3%
 
L2784681.3%
 
m2766201.3%
 
f2428621.2%
 
p2237511.1%
 
Other values (10)8056383.9%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter1751926783.9%
 
Uppercase Letter262382812.6%
 
Space Separator5766402.8%
 
Other Punctuation1667230.8%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
M49052818.7%
 
D42902816.4%
 
B42902816.4%
 
U31433512.0%
 
A28145510.7%
 
L27846810.6%
 
E1476125.6%
 
C1373065.2%
 
S566652.2%
 
R334551.3%
 
P144480.6%
 
F115000.4%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n279651716.0%
 
i263615615.0%
 
e188680610.8%
 
s185065110.6%
 
r13553127.7%
 
g12055566.9%
 
u9080375.2%
 
l7566804.3%
 
o7175324.1%
 
a4668542.7%
 
t4336722.5%
 
b4290282.4%
 
d4280682.4%
 
h3396351.9%
 
c3276011.9%
 
m2766201.6%
 
f2428621.4%
 
p2237511.3%
 
q1476120.8%
 
k643690.4%
 
w259480.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
576640100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/166723100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin2014309596.4%
 
Common7433633.6%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n279651713.9%
 
i263615613.1%
 
e18868069.4%
 
s18506519.2%
 
r13553126.7%
 
g12055566.0%
 
u9080374.5%
 
l7566803.8%
 
o7175323.6%
 
M4905282.4%
 
a4668542.3%
 
t4336722.2%
 
D4290282.1%
 
b4290282.1%
 
B4290282.1%
 
d4280682.1%
 
h3396351.7%
 
c3276011.6%
 
U3143351.6%
 
A2814551.4%
 
L2784681.4%
 
m2766201.4%
 
f2428621.2%
 
p2237511.1%
 
E1476120.7%
 
Other values (8)4913032.4%
 

Most frequent Common characters

ValueCountFrequency (%) 
57664077.6%
 
/16672322.4%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII20886458100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n279651713.4%
 
i263615612.6%
 
e18868069.0%
 
s18506518.9%
 
r13553126.5%
 
g12055565.8%
 
u9080374.3%
 
l7566803.6%
 
o7175323.4%
 
5766402.8%
 
M4905282.3%
 
a4668542.2%
 
t4336722.1%
 
D4290282.1%
 
b4290282.1%
 
B4290282.1%
 
d4280682.0%
 
h3396351.6%
 
c3276011.6%
 
U3143351.5%
 
A2814551.3%
 
L2784681.3%
 
m2766201.3%
 
f2428621.2%
 
p2237511.1%
 
Other values (10)8056383.9%
 

CONT_DATE
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct8760
Distinct (%)0.9%
Missing891531
Missing (%)47.4%
Infinite0
Infinite (%)0.0%
Mean2453237.753
Minimum2448622.5
Maximum2457391.5
Zeros0
Zeros (%)0.0%
Memory size14.3 MiB
2020-11-18T18:04:24.959773image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum2448622.5
5-th percentile2449059.5
Q12450700.75
median2453466.5
Q32455753.5
95-th percentile2457106.5
Maximum2457391.5
Range8769
Interquartile range (IQR)5052.75

Descriptive statistics

Standard deviation2687.547698
Coefficient of variation (CV)0.001095510492
Kurtosis-1.324652733
Mean2453237.753
Median Absolute Deviation (MAD)2419
Skewness-0.1209844344
Sum2.426090224e+12
Variance7222912.628
MonotocityNot monotonic
2020-11-18T18:04:25.111816image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
2455611.5841< 0.1%
 
2457067.5668< 0.1%
 
2449056.5649< 0.1%
 
2456367.5631< 0.1%
 
2450137.5631< 0.1%
 
2448683.5631< 0.1%
 
2449430.5605< 0.1%
 
2455606.5594< 0.1%
 
2450309.5593< 0.1%
 
2450138.5588< 0.1%
 
2449557.5584< 0.1%
 
2456112.5578< 0.1%
 
2457112.5574< 0.1%
 
2454575.5530< 0.1%
 
2456730.5529< 0.1%
 
2453476.5528< 0.1%
 
2450146.5527< 0.1%
 
2456731.5524< 0.1%
 
2449556.5522< 0.1%
 
2457146.5517< 0.1%
 
2450127.5517< 0.1%
 
2450165.5516< 0.1%
 
2449773.5515< 0.1%
 
2457113.5515< 0.1%
 
2455612.5507< 0.1%
 
Other values (8735)97452051.8%
 
(Missing)89153147.4%
 
ValueCountFrequency (%) 
2448622.570< 0.1%
 
2448623.522< 0.1%
 
2448624.523< 0.1%
 
2448625.544< 0.1%
 
2448626.529< 0.1%
 
2448627.567< 0.1%
 
2448628.5103< 0.1%
 
2448629.545< 0.1%
 
2448630.516< 0.1%
 
2448631.541< 0.1%
 
ValueCountFrequency (%) 
2457391.51< 0.1%
 
2457388.51< 0.1%
 
2457387.520< 0.1%
 
2457386.515< 0.1%
 
2457385.524< 0.1%
 
2457384.521< 0.1%
 
2457383.510< 0.1%
 
2457382.518< 0.1%
 
2457381.519< 0.1%
 
2457380.526< 0.1%
 

CONT_DOY
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct366
Distinct (%)< 0.1%
Missing891531
Missing (%)47.4%
Infinite0
Infinite (%)0.0%
Mean172.6567658
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Memory size14.3 MiB
2020-11-18T18:04:25.275783image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile39
Q1102
median181
Q3232
95-th percentile316
Maximum366
Range365
Interquartile range (IQR)130

Descriptive statistics

Standard deviation84.32034771
Coefficient of variation (CV)0.4883697858
Kurtosis-0.8031035961
Mean172.6567658
Median Absolute Deviation (MAD)65
Skewness0.06155756373
Sum170746146
Variance7109.921038
MonotocityNot monotonic
2020-11-18T18:04:25.437817image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
18573250.4%
 
18670910.4%
 
18453890.3%
 
18752680.3%
 
20452460.3%
 
20552150.3%
 
21651810.3%
 
21451810.3%
 
20651460.3%
 
21551430.3%
 
21851310.3%
 
21951130.3%
 
21751040.3%
 
20250890.3%
 
22050640.3%
 
18349810.3%
 
20349800.3%
 
22749100.3%
 
22248630.3%
 
21048610.3%
 
20748590.3%
 
20148430.3%
 
21248180.3%
 
22448130.3%
 
20047930.3%
 
Other values (341)85852745.7%
 
(Missing)89153147.4%
 
ValueCountFrequency (%) 
110880.1%
 
2805< 0.1%
 
3803< 0.1%
 
4899< 0.1%
 
59560.1%
 
69630.1%
 
710220.1%
 
89850.1%
 
99590.1%
 
10891< 0.1%
 
ValueCountFrequency (%) 
366135< 0.1%
 
365778< 0.1%
 
364672< 0.1%
 
363730< 0.1%
 
362877< 0.1%
 
361842< 0.1%
 
360737< 0.1%
 
359523< 0.1%
 
358552< 0.1%
 
357687< 0.1%
 

CONT_TIME
Categorical

HIGH CARDINALITY
MISSING

Distinct1441
Distinct (%)0.2%
Missing972173
Missing (%)51.7%
Memory size14.3 MiB
1800
 
38078
1600
 
22167
1700
 
20606
1200
 
19276
1500
 
18757
Other values (1436)
789408 
ValueCountFrequency (%) 
1800380782.0%
 
1600221671.2%
 
1700206061.1%
 
1200192761.0%
 
1500187571.0%
 
2000173150.9%
 
1400162340.9%
 
1900153540.8%
 
1630143670.8%
 
1300129630.7%
 
1530121130.6%
 
1730116640.6%
 
1830104820.6%
 
1430103010.5%
 
210099350.5%
 
100090250.5%
 
220087980.5%
 
110081740.4%
 
193081700.4%
 
133079990.4%
 
123066710.4%
 
203065120.3%
 
230058500.3%
 
080056300.3%
 
113052640.3%
 
Other values (1416)58658731.2%
 
(Missing)97217351.7%
 
2020-11-18T18:04:25.625817image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-18T18:04:25.794816image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length3
Mean length3.482206263
Min length0

Overview of Unicode Properties

Unique unicode characters12
Unique unicode categories2 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n194434629.7%
 
a97217314.8%
 
194024914.4%
 
092926414.2%
 
23503945.4%
 
53439425.3%
 
33158104.8%
 
42407733.7%
 
81397912.1%
 
61383752.1%
 
71257451.9%
 
91073051.6%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number363164855.5%
 
Lowercase Letter291651944.5%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
194024925.9%
 
092926425.6%
 
23503949.6%
 
53439429.5%
 
33158108.7%
 
42407736.6%
 
81397913.8%
 
61383753.8%
 
71257453.5%
 
91073053.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n194434666.7%
 
a97217333.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common363164855.5%
 
Latin291651944.5%
 

Most frequent Common characters

ValueCountFrequency (%) 
194024925.9%
 
092926425.6%
 
23503949.6%
 
53439429.5%
 
33158108.7%
 
42407736.6%
 
81397913.8%
 
61383753.8%
 
71257453.5%
 
91073053.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n194434666.7%
 
a97217333.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII6548167100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n194434629.7%
 
a97217314.8%
 
194024914.4%
 
092926414.2%
 
23503945.4%
 
53439425.3%
 
33158104.8%
 
42407733.7%
 
81397912.1%
 
61383752.1%
 
71257451.9%
 
91073051.6%
 

FIRE_SIZE
Real number (ℝ≥0)

SKEWED

Distinct13637
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74.52015834
Minimum1e-05
Maximum606945
Zeros0
Zeros (%)0.0%
Memory size14.3 MiB
2020-11-18T18:04:25.947787image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1e-05
5-th percentile0.1
Q10.1
median1
Q33.3
95-th percentile45
Maximum606945
Range606945
Interquartile range (IQR)3.2

Descriptive statistics

Standard deviation2497.59818
Coefficient of variation (CV)33.51573904
Kurtosis16159.39785
Mean74.52015834
Median Absolute Deviation (MAD)0.9
Skewness106.83733
Sum140132549.6
Variance6237996.668
MonotocityNot monotonic
2020-11-18T18:04:26.110817image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.145914524.4%
 
122168011.8%
 
0.51132226.0%
 
21094935.8%
 
0.2753024.0%
 
3657843.5%
 
5619633.3%
 
0.25543252.9%
 
0.3529732.8%
 
4381912.0%
 
0.01354581.9%
 
10352151.9%
 
1.5262701.4%
 
15204741.1%
 
20201071.1%
 
6194901.0%
 
8164220.9%
 
7127790.7%
 
25122310.7%
 
0.4120390.6%
 
30118970.6%
 
2.598460.5%
 
1296480.5%
 
4089050.5%
 
5080570.4%
 
Other values (13612)36954919.7%
 
ValueCountFrequency (%) 
1e-051< 0.1%
 
9e-051< 0.1%
 
0.000113< 0.1%
 
0.00024< 0.1%
 
0.000221< 0.1%
 
0.000342< 0.1%
 
0.00041< 0.1%
 
0.0004591< 0.1%
 
0.00081< 0.1%
 
0.00091< 0.1%
 
ValueCountFrequency (%) 
6069451< 0.1%
 
558198.31< 0.1%
 
5380491< 0.1%
 
5376271< 0.1%
 
5170781< 0.1%
 
4999451< 0.1%
 
4832801< 0.1%
 
4795491< 0.1%
 
4639941< 0.1%
 
4610471< 0.1%
 

FIRE_SIZE_CLASS
Categorical

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size14.3 MiB
B
939376 
A
666919 
C
220077 
D
 
28427
E
 
14107
Other values (2)
 
11559
ValueCountFrequency (%) 
B93937650.0%
 
A66691935.5%
 
C22007711.7%
 
D284271.5%
 
E141070.8%
 
F77860.4%
 
G37730.2%
 
2020-11-18T18:04:26.260820image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-18T18:04:26.343817image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:04:26.458834image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories1 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
B93937650.0%
 
A66691935.5%
 
C22007711.7%
 
D284271.5%
 
E141070.8%
 
F77860.4%
 
G37730.2%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter1880465100.0%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
B93937650.0%
 
A66691935.5%
 
C22007711.7%
 
D284271.5%
 
E141070.8%
 
F77860.4%
 
G37730.2%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin1880465100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
B93937650.0%
 
A66691935.5%
 
C22007711.7%
 
D284271.5%
 
E141070.8%
 
F77860.4%
 
G37730.2%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1880465100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
B93937650.0%
 
A66691935.5%
 
C22007711.7%
 
D284271.5%
 
E141070.8%
 
F77860.4%
 
G37730.2%
 

LATITUDE
Real number (ℝ≥0)

Distinct894061
Distinct (%)47.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.78121281
Minimum17.93972222
Maximum70.3306
Zeros0
Zeros (%)0.0%
Memory size14.3 MiB
2020-11-18T18:04:27.069835image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum17.93972222
5-th percentile29.21543111
Q132.8186
median35.4525
Q340.8272
95-th percentile47.204088
Maximum70.3306
Range52.39087778
Interquartile range (IQR)8.0086

Descriptive statistics

Standard deviation6.139031271
Coefficient of variation (CV)0.1669067114
Kurtosis1.910779023
Mean36.78121281
Median Absolute Deviation (MAD)3.54222
Skewness0.4883635083
Sum69165783.34
Variance37.68770494
MonotocityNot monotonic
2020-11-18T18:04:27.218800image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
47.86669550.1%
 
33.3353706< 0.1%
 
33.3517605< 0.1%
 
47.8833585< 0.1%
 
17.970539571< 0.1%
 
35.3526< 0.1%
 
33.925517< 0.1%
 
35.6833496< 0.1%
 
41.0665495< 0.1%
 
33.3167471< 0.1%
 
35.35445< 0.1%
 
36.975429< 0.1%
 
34.01194444420< 0.1%
 
34.9416< 0.1%
 
35.3167415< 0.1%
 
35.2407< 0.1%
 
36.98888888399< 0.1%
 
35.2667393< 0.1%
 
35.2833392< 0.1%
 
33.3667390< 0.1%
 
17.993565384< 0.1%
 
35.25384< 0.1%
 
35.3333380< 0.1%
 
36.05888888376< 0.1%
 
35.7374< 0.1%
 
Other values (894036)186853499.4%
 
ValueCountFrequency (%) 
17.939722221< 0.1%
 
17.9449241< 0.1%
 
17.951< 0.1%
 
17.9513891< 0.1%
 
17.951941< 0.1%
 
17.9538891< 0.1%
 
17.955277781< 0.1%
 
17.956533164< 0.1%
 
17.9566671< 0.1%
 
17.9571411< 0.1%
 
ValueCountFrequency (%) 
70.33061< 0.1%
 
70.13811< 0.1%
 
70.13781< 0.1%
 
69.84951< 0.1%
 
69.78281< 0.1%
 
69.777451< 0.1%
 
69.61891< 0.1%
 
69.46811< 0.1%
 
69.45251< 0.1%
 
69.4331< 0.1%
 

LONGITUDE
Real number (ℝ)

Distinct997536
Distinct (%)53.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-95.70494159
Minimum-178.8026
Maximum-65.25694444
Zeros0
Zeros (%)0.0%
Memory size14.3 MiB
2020-11-18T18:04:27.941834image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-178.8026
5-th percentile-122.035
Q1-110.36347
median-92.043043
Q3-82.2976
95-th percentile-74.2012
Maximum-65.25694444
Range113.5456556
Interquartile range (IQR)28.06587

Descriptive statistics

Standard deviation16.71694396
Coefficient of variation (CV)-0.1746716908
Kurtosis0.1398536113
Mean-95.70494159
Median Absolute Deviation (MAD)10.981916
Skewness-0.7172878416
Sum-179969793
Variance279.4562154
MonotocityNot monotonic
2020-11-18T18:04:28.093834image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-110.4518792< 0.1%
 
-123.6845745< 0.1%
 
-66.246414571< 0.1%
 
-110.4507507< 0.1%
 
-66.386131384< 0.1%
 
-123.6678371< 0.1%
 
-81.9358< 0.1%
 
-95.0169356< 0.1%
 
-79.75355< 0.1%
 
-66.114357352< 0.1%
 
-116.8347338< 0.1%
 
-81.7329< 0.1%
 
-66.172852326< 0.1%
 
-110.4573320< 0.1%
 
-94.9003314< 0.1%
 
-81.8307< 0.1%
 
-82306< 0.1%
 
-79.7667301< 0.1%
 
-81.95299< 0.1%
 
-81.97294< 0.1%
 
-79.7294< 0.1%
 
-81.65292< 0.1%
 
-81.25292< 0.1%
 
-79.8288< 0.1%
 
-81.2285< 0.1%
 
Other values (997511)187108999.5%
 
ValueCountFrequency (%) 
-178.80261< 0.1%
 
-173.38571< 0.1%
 
-170.36941< 0.1%
 
-168.871< 0.1%
 
-166.86941< 0.1%
 
-166.26931< 0.1%
 
-166.16671< 0.1%
 
-166.15271< 0.1%
 
-166.151< 0.1%
 
-166.0531< 0.1%
 
ValueCountFrequency (%) 
-65.256944441< 0.1%
 
-65.2641756< 0.1%
 
-65.270277781< 0.1%
 
-65.273611111< 0.1%
 
-65.274444441< 0.1%
 
-65.2748953< 0.1%
 
-65.275555561< 0.1%
 
-65.278888891< 0.1%
 
-65.285833333< 0.1%
 
-65.28751< 0.1%
 

OWNER_CODE
Real number (ℝ≥0)

Distinct16
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.59657797
Minimum0
Maximum15
Zeros15
Zeros (%)< 0.1%
Memory size14.3 MiB
2020-11-18T18:04:28.225837image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q18
median14
Q314
95-th percentile14
Maximum15
Range15
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.404662212
Coefficient of variation (CV)0.4156683622
Kurtosis-0.8057555661
Mean10.59657797
Median Absolute Deviation (MAD)0
Skewness-0.827545277
Sum19926494
Variance19.4010492
MonotocityNot monotonic
2020-11-18T18:04:28.339833image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%) 
14105083555.9%
 
831482216.7%
 
518833810.0%
 
21068195.7%
 
13718813.8%
 
1632783.4%
 
7307901.6%
 
3175240.9%
 
4121910.6%
 
989520.5%
 
664520.3%
 
1242360.2%
 
1522060.1%
 
1118410.1%
 
10285< 0.1%
 
015< 0.1%
 
ValueCountFrequency (%) 
015< 0.1%
 
1632783.4%
 
21068195.7%
 
3175240.9%
 
4121910.6%
 
518833810.0%
 
664520.3%
 
7307901.6%
 
831482216.7%
 
989520.5%
 
ValueCountFrequency (%) 
1522060.1%
 
14105083555.9%
 
13718813.8%
 
1242360.2%
 
1118410.1%
 
10285< 0.1%
 
989520.5%
 
831482216.7%
 
7307901.6%
 
664520.3%
 

OWNER_DESCR
Categorical

Distinct16
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size14.3 MiB
MISSING/NOT SPECIFIED
1050835 
PRIVATE
314822 
USFS
188338 
BIA
106819 
STATE OR PRIVATE
 
71881
Other values (11)
147770 
ValueCountFrequency (%) 
MISSING/NOT SPECIFIED105083555.9%
 
PRIVATE31482216.7%
 
USFS18833810.0%
 
BIA1068195.7%
 
STATE OR PRIVATE718813.8%
 
BLM632783.4%
 
STATE307901.6%
 
NPS175240.9%
 
FWS121910.6%
 
TRIBAL89520.5%
 
OTHER FEDERAL64520.3%
 
MUNICIPAL/LOCAL42360.2%
 
UNDEFINED FEDERAL22060.1%
 
COUNTY18410.1%
 
BOR285< 0.1%
 
FOREIGN15< 0.1%
 
2020-11-18T18:04:28.463805image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-18T18:04:28.615062image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length21
Median length21
Mean length14.45321184
Min length3

Overview of Unicode Properties

Unique unicode characters23
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
I471650717.4%
 
S366156713.5%
 
E26192399.6%
 
N21296987.8%
 
T16601256.1%
 
P14592985.4%
 
F12622434.6%
 
12032554.4%
 
O11355454.2%
 
M11183494.1%
 
D10639053.9%
 
C10611483.9%
 
/10550713.9%
 
G10508503.9%
 
A6222752.3%
 
R4829461.8%
 
V3867031.4%
 
U1966210.7%
 
B1793340.7%
 
L935960.3%
 
W12191< 0.1%
 
H6452< 0.1%
 
Y1841< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter2492043391.7%
 
Space Separator12032554.4%
 
Other Punctuation10550713.9%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
I471650718.9%
 
S366156714.7%
 
E261923910.5%
 
N21296988.5%
 
T16601256.7%
 
P14592985.9%
 
F12622435.1%
 
O11355454.6%
 
M11183494.5%
 
D10639054.3%
 
C10611484.3%
 
G10508504.2%
 
A6222752.5%
 
R4829461.9%
 
V3867031.6%
 
U1966210.8%
 
B1793340.7%
 
L935960.4%
 
W12191< 0.1%
 
H6452< 0.1%
 
Y1841< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
1203255100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/1055071100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin2492043391.7%
 
Common22583268.3%
 

Most frequent Latin characters

ValueCountFrequency (%) 
I471650718.9%
 
S366156714.7%
 
E261923910.5%
 
N21296988.5%
 
T16601256.7%
 
P14592985.9%
 
F12622435.1%
 
O11355454.6%
 
M11183494.5%
 
D10639054.3%
 
C10611484.3%
 
G10508504.2%
 
A6222752.5%
 
R4829461.9%
 
V3867031.6%
 
U1966210.8%
 
B1793340.7%
 
L935960.4%
 
W12191< 0.1%
 
H6452< 0.1%
 
Y1841< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
120325553.3%
 
/105507146.7%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII27178759100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
I471650717.4%
 
S366156713.5%
 
E26192399.6%
 
N21296987.8%
 
T16601256.1%
 
P14592985.4%
 
F12622434.6%
 
12032554.4%
 
O11355454.2%
 
M11183494.1%
 
D10639053.9%
 
C10611483.9%
 
/10550713.9%
 
G10508503.9%
 
A6222752.3%
 
R4829461.8%
 
V3867031.4%
 
U1966210.7%
 
B1793340.7%
 
L935960.3%
 
W12191< 0.1%
 
H6452< 0.1%
 
Y1841< 0.1%
 

STATE
Categorical

HIGH CARDINALITY

Distinct52
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size14.3 MiB
CA
189550 
GA
168867 
TX
142021 
NC
 
111277
FL
 
90261
Other values (47)
1178489 
ValueCountFrequency (%) 
CA18955010.1%
 
GA1688679.0%
 
TX1420217.6%
 
NC1112775.9%
 
FL902614.8%
 
SC813154.3%
 
NY808704.3%
 
MS792304.2%
 
AZ715863.8%
 
AL665703.5%
 
OR610883.2%
 
MN447692.4%
 
OK432392.3%
 
MT407672.2%
 
NM374782.0%
 
ID366982.0%
 
CO341571.8%
 
WA335131.8%
 
WI318611.7%
 
AR316631.7%
 
TN311541.7%
 
SD309631.6%
 
UT307251.6%
 
LA300131.6%
 
KY270891.4%
 
Other values (27)25374113.5%
 
2020-11-18T18:04:28.808577image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-18T18:04:28.968591image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length2
Min length2

Overview of Unicode Properties

Unique unicode characters24
Unique unicode categories1 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
A64191017.1%
 
C42134111.2%
 
N37617710.0%
 
T2500996.6%
 
M2500976.6%
 
S1991815.3%
 
L1891715.0%
 
G1688674.5%
 
O1599164.3%
 
X1420213.8%
 
Y1221253.2%
 
R1153123.1%
 
W1015072.7%
 
I979952.6%
 
K908442.4%
 
F902612.4%
 
D867212.3%
 
Z715861.9%
 
V612121.6%
 
P307930.8%
 
U307250.8%
 
J259490.7%
 
E212940.6%
 
H158260.4%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter3760930100.0%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
A64191017.1%
 
C42134111.2%
 
N37617710.0%
 
T2500996.6%
 
M2500976.6%
 
S1991815.3%
 
L1891715.0%
 
G1688674.5%
 
O1599164.3%
 
X1420213.8%
 
Y1221253.2%
 
R1153123.1%
 
W1015072.7%
 
I979952.6%
 
K908442.4%
 
F902612.4%
 
D867212.3%
 
Z715861.9%
 
V612121.6%
 
P307930.8%
 
U307250.8%
 
J259490.7%
 
E212940.6%
 
H158260.4%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin3760930100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
A64191017.1%
 
C42134111.2%
 
N37617710.0%
 
T2500996.6%
 
M2500976.6%
 
S1991815.3%
 
L1891715.0%
 
G1688674.5%
 
O1599164.3%
 
X1420213.8%
 
Y1221253.2%
 
R1153123.1%
 
W1015072.7%
 
I979952.6%
 
K908442.4%
 
F902612.4%
 
D867212.3%
 
Z715861.9%
 
V612121.6%
 
P307930.8%
 
U307250.8%
 
J259490.7%
 
E212940.6%
 
H158260.4%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII3760930100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
A64191017.1%
 
C42134111.2%
 
N37617710.0%
 
T2500996.6%
 
M2500976.6%
 
S1991815.3%
 
L1891715.0%
 
G1688674.5%
 
O1599164.3%
 
X1420213.8%
 
Y1221253.2%
 
R1153123.1%
 
W1015072.7%
 
I979952.6%
 
K908442.4%
 
F902612.4%
 
D867212.3%
 
Z715861.9%
 
V612121.6%
 
P307930.8%
 
U307250.8%
 
J259490.7%
 
E212940.6%
 
H158260.4%
 

COUNTY
Categorical

HIGH CARDINALITY
MISSING

Distinct3455
Distinct (%)0.3%
Missing678148
Missing (%)36.1%
Memory size14.3 MiB
5
 
7576
Lincoln
 
7405
SUFFOLK
 
7373
Polk
 
6955
Washington
 
6916
Other values (3450)
1166092 
ValueCountFrequency (%) 
575760.4%
 
Lincoln74050.4%
 
SUFFOLK73730.4%
 
Polk69550.4%
 
Washington69160.4%
 
Cherokee67960.4%
 
Oahu67770.4%
 
Marion66570.4%
 
Jackson63050.3%
 
Lee59140.3%
 
Ocean49370.3%
 
Clay46550.2%
 
2946170.2%
 
Wayne43060.2%
 
Jefferson42260.2%
 
Jasper40540.2%
 
McCurtain40390.2%
 
1740170.2%
 
Harrison40080.2%
 
MONROE39920.2%
 
4939130.2%
 
St. Louis38950.2%
 
ORANGE38480.2%
 
Cass37940.2%
 
Taylor37150.2%
 
Other values (3430)107162757.0%
 
(Missing)67814836.1%
 
2020-11-18T18:04:29.134698image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique392 ?
Unique (%)< 0.1%
2020-11-18T18:04:29.298704image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length50
Median length4
Mean length5.641060057
Min length1

Overview of Unicode Properties

Unique unicode characters72
Unique unicode categories9 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n185526017.5%
 
a129678712.2%
 
9351558.8%
 
e5837485.5%
 
o4959204.7%
 
r4150593.9%
 
l3509173.3%
 
i3262373.1%
 
t2910972.7%
 
s2742372.6%
 
u1895261.8%
 
C1845731.7%
 
S1606611.5%
 
h1595561.5%
 
A1556751.5%
 
E1494691.4%
 
d1417081.3%
 
c1380421.3%
 
L1324541.2%
 
O1271781.2%
 
R1269131.2%
 
N1242691.2%
 
M1189231.1%
 
k1066061.0%
 
m1058291.0%
 
Other values (47)166201715.7%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter721474368.0%
 
Uppercase Letter213058720.1%
 
Space Separator9351558.8%
 
Decimal Number3194483.0%
 
Other Punctuation72700.1%
 
Dash Punctuation565< 0.1%
 
Connector Punctuation28< 0.1%
 
Open Punctuation10< 0.1%
 
Close Punctuation10< 0.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
15442217.0%
 
34878815.3%
 
04106012.9%
 
53444010.8%
 
93281310.3%
 
7305089.6%
 
2281748.8%
 
4201216.3%
 
6150804.7%
 
8140424.4%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n185526025.7%
 
a129678718.0%
 
e5837488.1%
 
o4959206.9%
 
r4150595.8%
 
l3509174.9%
 
i3262374.5%
 
t2910974.0%
 
s2742373.8%
 
u1895262.6%
 
h1595562.2%
 
d1417082.0%
 
c1380421.9%
 
k1066061.5%
 
m1058291.5%
 
y1023241.4%
 
g915211.3%
 
w641500.9%
 
b607910.8%
 
f542310.8%
 
p468360.6%
 
v418480.6%
 
x128740.2%
 
q55570.1%
 
z38360.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
C1845738.7%
 
S1606617.5%
 
A1556757.3%
 
E1494697.0%
 
L1324546.2%
 
O1271786.0%
 
R1269136.0%
 
N1242695.8%
 
M1189235.6%
 
B930184.4%
 
T900534.2%
 
H854434.0%
 
W787803.7%
 
D734803.4%
 
P680593.2%
 
I633203.0%
 
G612692.9%
 
U532392.5%
 
F516392.4%
 
K436952.1%
 
J395091.9%
 
Y194370.9%
 
V170250.8%
 
Q55320.3%
 
X44010.2%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
935155100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.664291.4%
 
'2994.1%
 
&2873.9%
 
,240.3%
 
/180.2%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(10100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)10100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-565100.0%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_28100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin934533088.1%
 
Common126248611.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
93515574.1%
 
1544224.3%
 
3487883.9%
 
0410603.3%
 
5344402.7%
 
9328132.6%
 
7305082.4%
 
2281742.2%
 
4201211.6%
 
6150801.2%
 
8140421.1%
 
.66420.5%
 
-565< 0.1%
 
'299< 0.1%
 
&287< 0.1%
 
_28< 0.1%
 
,24< 0.1%
 
/18< 0.1%
 
(10< 0.1%
 
)10< 0.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n185526019.9%
 
a129678713.9%
 
e5837486.2%
 
o4959205.3%
 
r4150594.4%
 
l3509173.8%
 
i3262373.5%
 
t2910973.1%
 
s2742372.9%
 
u1895262.0%
 
C1845732.0%
 
S1606611.7%
 
h1595561.7%
 
A1556751.7%
 
E1494691.6%
 
d1417081.5%
 
c1380421.5%
 
L1324541.4%
 
O1271781.4%
 
R1269131.4%
 
N1242691.3%
 
M1189231.3%
 
k1066061.1%
 
m1058291.1%
 
y1023241.1%
 
Other values (27)123236213.2%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII10607816100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n185526017.5%
 
a129678712.2%
 
9351558.8%
 
e5837485.5%
 
o4959204.7%
 
r4150593.9%
 
l3509173.3%
 
i3262373.1%
 
t2910972.7%
 
s2742372.6%
 
u1895261.8%
 
C1845731.7%
 
S1606611.5%
 
h1595561.5%
 
A1556751.5%
 
E1494691.4%
 
d1417081.3%
 
c1380421.3%
 
L1324541.2%
 
O1271781.2%
 
R1269131.2%
 
N1242691.2%
 
M1189231.1%
 
k1066061.0%
 
m1058291.0%
 
Other values (47)166201715.7%
 

FIPS_CODE
Categorical

HIGH CARDINALITY
MISSING

Distinct285
Distinct (%)< 0.1%
Missing678148
Missing (%)36.1%
Memory size14.3 MiB
005
 
29069
003
 
28850
029
 
28519
001
 
27042
007
 
22230
Other values (280)
1066607 
ValueCountFrequency (%) 
005290691.5%
 
003288501.5%
 
029285191.5%
 
001270421.4%
 
007222301.2%
 
019219091.2%
 
017217761.2%
 
015213211.1%
 
035207101.1%
 
021194111.0%
 
039190961.0%
 
065186161.0%
 
027182651.0%
 
037182511.0%
 
089182231.0%
 
013176460.9%
 
103172350.9%
 
025166050.9%
 
049165050.9%
 
047164160.9%
 
071159520.8%
 
085158620.8%
 
009158470.8%
 
063156540.8%
 
023153760.8%
 
Other values (260)70593137.5%
 
(Missing)67814836.1%
 
2020-11-18T18:04:29.469861image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique6 ?
Unique (%)< 0.1%
2020-11-18T18:04:29.600873image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length2.999999468
Min length2

Overview of Unicode Properties

Unique unicode characters12
Unique unicode categories2 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n135629624.0%
 
0100331417.8%
 
a67814812.0%
 
164009611.3%
 
34085177.2%
 
53551746.3%
 
73263295.8%
 
93134345.6%
 
22291944.1%
 
41364892.4%
 
6999751.8%
 
8944281.7%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number360695063.9%
 
Lowercase Letter203444436.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
0100331427.8%
 
164009617.7%
 
340851711.3%
 
53551749.8%
 
73263299.0%
 
93134348.7%
 
22291946.4%
 
41364893.8%
 
6999752.8%
 
8944282.6%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n135629666.7%
 
a67814833.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common360695063.9%
 
Latin203444436.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
0100331427.8%
 
164009617.7%
 
340851711.3%
 
53551749.8%
 
73263299.0%
 
93134348.7%
 
22291946.4%
 
41364893.8%
 
6999752.8%
 
8944282.6%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n135629666.7%
 
a67814833.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII5641394100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n135629624.0%
 
0100331417.8%
 
a67814812.0%
 
164009611.3%
 
34085177.2%
 
53551746.3%
 
73263295.8%
 
93134345.6%
 
22291944.1%
 
41364892.4%
 
6999751.8%
 
8944281.7%
 

FIPS_NAME
Categorical

HIGH CARDINALITY
MISSING

Distinct1698
Distinct (%)0.1%
Missing678148
Missing (%)36.1%
Memory size14.3 MiB
Washington
 
11014
Lincoln
 
10571
Jackson
 
9902
Marion
 
8908
Cherokee
 
8558
Other values (1693)
1153364 
ValueCountFrequency (%) 
Washington110140.6%
 
Lincoln105710.6%
 
Jackson99020.5%
 
Marion89080.5%
 
Cherokee85580.5%
 
Polk83000.4%
 
Monroe81730.4%
 
Coconino79000.4%
 
Jefferson77700.4%
 
Suffolk75970.4%
 
Lee70490.4%
 
Riverside69250.4%
 
Honolulu67800.4%
 
Wayne65420.3%
 
Orange61860.3%
 
Douglas61400.3%
 
Jasper57520.3%
 
Lake55490.3%
 
Clay53230.3%
 
Columbia52790.3%
 
Richmond51130.3%
 
Franklin49920.3%
 
Ocean49410.3%
 
Union49010.3%
 
Laurens48690.3%
 
Other values (1673)102728354.6%
 
(Missing)67814836.1%
 
2020-11-18T18:04:29.743150image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique36 ?
Unique (%)< 0.1%
2020-11-18T18:04:29.891119image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length31
Median length5
Mean length5.554020415
Min length3

Overview of Unicode Properties

Unique unicode characters57
Unique unicode categories7 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n203656819.5%
 
a152487714.6%
 
e8135237.8%
 
o6781846.5%
 
r5648935.4%
 
l4856404.6%
 
i4418924.2%
 
s3837813.7%
 
t3580493.4%
 
u2413832.3%
 
h2054732.0%
 
c1971411.9%
 
d1926111.8%
 
C1576491.5%
 
k1498421.4%
 
m1423151.4%
 
g1365031.3%
 
S1139121.1%
 
M1131141.1%
 
y1039941.0%
 
L960960.9%
 
B901640.9%
 
b832770.8%
 
814540.8%
 
w809730.8%
 
Other values (32)9708339.3%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter905354886.7%
 
Uppercase Letter129610912.4%
 
Space Separator814540.8%
 
Other Punctuation114000.1%
 
Dash Punctuation1628< 0.1%
 
Open Punctuation1< 0.1%
 
Close Punctuation1< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
C15764912.2%
 
S1139128.8%
 
M1131148.7%
 
L960967.4%
 
B901647.0%
 
W770635.9%
 
H722515.6%
 
P701795.4%
 
R540234.2%
 
D538854.2%
 
A522504.0%
 
J471433.6%
 
T447783.5%
 
G437073.4%
 
O392653.0%
 
F337432.6%
 
E297272.3%
 
K270962.1%
 
N248561.9%
 
I160941.2%
 
U150011.2%
 
V100750.8%
 
Y94790.7%
 
Q33270.3%
 
Z12320.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n203656822.5%
 
a152487716.8%
 
e8135239.0%
 
o6781847.5%
 
r5648936.2%
 
l4856405.4%
 
i4418924.9%
 
s3837814.2%
 
t3580494.0%
 
u2413832.7%
 
h2054732.3%
 
c1971412.2%
 
d1926112.1%
 
k1498421.7%
 
m1423151.6%
 
g1365031.5%
 
y1039941.1%
 
b832770.9%
 
w809730.9%
 
f805260.9%
 
p606350.7%
 
v572830.6%
 
x187680.2%
 
q82250.1%
 
z59760.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
81454100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.1098496.4%
 
'4163.6%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-1628100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(1100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)1100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin1034965799.1%
 
Common944840.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n203656819.7%
 
a152487714.7%
 
e8135237.9%
 
o6781846.6%
 
r5648935.5%
 
l4856404.7%
 
i4418924.3%
 
s3837813.7%
 
t3580493.5%
 
u2413832.3%
 
h2054732.0%
 
c1971411.9%
 
d1926111.9%
 
C1576491.5%
 
k1498421.4%
 
m1423151.4%
 
g1365031.3%
 
S1139121.1%
 
M1131141.1%
 
y1039941.0%
 
L960960.9%
 
B901640.9%
 
b832770.8%
 
w809730.8%
 
f805260.8%
 
Other values (26)8772778.5%
 

Most frequent Common characters

ValueCountFrequency (%) 
8145486.2%
 
.1098411.6%
 
-16281.7%
 
'4160.4%
 
(1< 0.1%
 
)1< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII10444141100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n203656819.5%
 
a152487714.6%
 
e8135237.8%
 
o6781846.5%
 
r5648935.4%
 
l4856404.6%
 
i4418924.2%
 
s3837813.7%
 
t3580493.4%
 
u2413832.3%
 
h2054732.0%
 
c1971411.9%
 
d1926111.8%
 
C1576491.5%
 
k1498421.4%
 
m1423151.4%
 
g1365031.3%
 
S1139121.1%
 
M1131141.1%
 
y1039941.0%
 
L960960.9%
 
B901640.9%
 
b832770.8%
 
814540.8%
 
w809730.8%
 
Other values (32)9708339.3%
 

Shape
Categorical

HIGH CARDINALITY

Distinct1569708
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Memory size14.3 MiB
b'\x00\x01\xad\x10\x00\x00\xb0\xd19?\xc5\x8fP\xc0 ~p>u\xf81@\xb0\xd19?\xc5\x8fP\xc0 ~p>u\xf81@|\x01\x00\x00\x00\xb0\xd19?\xc5\x8fP\xc0 ~p>u\xf81@\xfe'
 
571
b'\x00\x01\xad\x10\x00\x000>\xcc^\xb6\x98P\xc0Ps\x9dFZ\xfe1@0>\xcc^\xb6\x98P\xc0Ps\x9dFZ\xfe1@|\x01\x00\x00\x000>\xcc^\xb6\x98P\xc0Ps\x9dFZ\xfe1@\xfe'
 
384
b'\x00\x01\xad\x10\x00\x00(\x87\x16\xd9\xce\xeb^\xc0\x98\x97n\x12\x83\x88D@(\x87\x16\xd9\xce\xeb^\xc0\x98\x97n\x12\x83\x88D@|\x01\x00\x00\x00(\x87\x16\xd9\xce\xeb^\xc0\x98\x97n\x12\x83\x88D@\xfe'
 
355
b'\x00\x01\xad\x10\x00\x00d\xc4\x05\xa0Q\x87P\xc0@\xb4s\x9a\x05\xfa1@d\xc4\x05\xa0Q\x87P\xc0@\xb4s\x9a\x05\xfa1@|\x01\x00\x00\x00d\xc4\x05\xa0Q\x87P\xc0@\xb4s\x9a\x05\xfa1@\xfe'
 
352
b'\x00\x01\xad\x10\x00\x00$~\x8c\xb9k5]\xc0\xb8Y\xf5\xb9\xdaJ@@$~\x8c\xb9k5]\xc0\xb8Y\xf5\xb9\xdaJ@@|\x01\x00\x00\x00$~\x8c\xb9k5]\xc0\xb8Y\xf5\xb9\xdaJ@@\xfe'
 
336
Other values (1569703)
1878467 
ValueCountFrequency (%) 
b'\x00\x01\xad\x10\x00\x00\xb0\xd19?\xc5\x8fP\xc0 ~p>u\xf81@\xb0\xd19?\xc5\x8fP\xc0 ~p>u\xf81@|\x01\x00\x00\x00\xb0\xd19?\xc5\x8fP\xc0 ~p>u\xf81@\xfe'571< 0.1%
 
b'\x00\x01\xad\x10\x00\x000>\xcc^\xb6\x98P\xc0Ps\x9dFZ\xfe1@0>\xcc^\xb6\x98P\xc0Ps\x9dFZ\xfe1@|\x01\x00\x00\x000>\xcc^\xb6\x98P\xc0Ps\x9dFZ\xfe1@\xfe'384< 0.1%
 
b'\x00\x01\xad\x10\x00\x00(\x87\x16\xd9\xce\xeb^\xc0\x98\x97n\x12\x83\x88D@(\x87\x16\xd9\xce\xeb^\xc0\x98\x97n\x12\x83\x88D@|\x01\x00\x00\x00(\x87\x16\xd9\xce\xeb^\xc0\x98\x97n\x12\x83\x88D@\xfe'355< 0.1%
 
b'\x00\x01\xad\x10\x00\x00d\xc4\x05\xa0Q\x87P\xc0@\xb4s\x9a\x05\xfa1@d\xc4\x05\xa0Q\x87P\xc0@\xb4s\x9a\x05\xfa1@|\x01\x00\x00\x00d\xc4\x05\xa0Q\x87P\xc0@\xb4s\x9a\x05\xfa1@\xfe'352< 0.1%
 
b'\x00\x01\xad\x10\x00\x00$~\x8c\xb9k5]\xc0\xb8Y\xf5\xb9\xdaJ@@$~\x8c\xb9k5]\xc0\xb8Y\xf5\xb9\xdaJ@@|\x01\x00\x00\x00$~\x8c\xb9k5]\xc0\xb8Y\xf5\xb9\xdaJ@@\xfe'336< 0.1%
 
b'\x00\x01\xad\x10\x00\x00\x14\xc3\xd5\x01\x10\x8bP\xc0\x00\xaa\xd5WW\xf51@\x14\xc3\xd5\x01\x10\x8bP\xc0\x00\xaa\xd5WW\xf51@|\x01\x00\x00\x00\x14\xc3\xd5\x01\x10\x8bP\xc0\x00\xaa\xd5WW\xf51@\xfe'326< 0.1%
 
b'\x00\x01\xad\x10\x00\x00P"\x89^F\x90P\xc0 Z\xd6\xfdc\t2@P"\x89^F\x90P\xc0 Z\xd6\xfdc\t2@|\x01\x00\x00\x00P"\x89^F\x90P\xc0 Z\xd6\xfdc\t2@\xfe'282< 0.1%
 
b'\x00\x01\xad\x10\x00\x00L\x15\x8cJ\xea\x9c[\xc0\xb0,C\x1c\xeb\xaa@@L\x15\x8cJ\xea\x9c[\xc0\xb0,C\x1c\xeb\xaa@@|\x01\x00\x00\x00L\x15\x8cJ\xea\x9c[\xc0\xb0,C\x1c\xeb\xaa@@\xfe'281< 0.1%
 
b'\x00\x01\xad\x10\x00\x00\x14\xc7\xdc\x10>CR\xc0\xa0\x12I\xf42\xbeD@\x14\xc7\xdc\x10>CR\xc0\xa0\x12I\xf42\xbeD@|\x01\x00\x00\x00\x14\xc7\xdc\x10>CR\xc0\xa0\x12I\xf42\xbeD@\xfe'253< 0.1%
 
b'\x00\x01\xad\x10\x00\x00\x08uX\xe1\x96\x97P\xc0P\xb3\xeb\xde\x8a\xf81@\x08uX\xe1\x96\x97P\xc0P\xb3\xeb\xde\x8a\xf81@|\x01\x00\x00\x00\x08uX\xe1\x96\x97P\xc0P\xb3\xeb\xde\x8a\xf81@\xfe'239< 0.1%
 
b'\x00\x01\xad\x10\x00\x00`]\xdcF\x03\xc0W\xc0h]\xdcF\x03\x00B@`]\xdcF\x03\xc0W\xc0h]\xdcF\x03\x00B@|\x01\x00\x00\x00`]\xdcF\x03\xc0W\xc0h]\xdcF\x03\x00B@\xfe'230< 0.1%
 
b'\x00\x01\xad\x10\x00\x00\xec\x8d!\x008\xbcP\xc0\xf0\xf9\xd3Fu\x0e2@\xec\x8d!\x008\xbcP\xc0\xf0\xf9\xd3Fu\x0e2@|\x01\x00\x00\x00\xec\x8d!\x008\xbcP\xc0\xf0\xf9\xd3Fu\x0e2@\xfe'208< 0.1%
 
b'\x00\x01\xad\x10\x00\x00\xc8\xa0\xda\xe0D\x9eP\xc0 \x9f\xad\x83\x83!2@\xc8\xa0\xda\xe0D\x9eP\xc0 \x9f\xad\x83\x83!2@|\x01\x00\x00\x00\xc8\xa0\xda\xe0D\x9eP\xc0 \x9f\xad\x83\x83!2@\xfe'201< 0.1%
 
b'\x00\x01\xad\x10\x00\x00D\xfe`\xe0\xb9\xaaP\xc0\x00\xa3\xe8\x81\x8f\x012@D\xfe`\xe0\xb9\xaaP\xc0\x00\xa3\xe8\x81\x8f\x012@|\x01\x00\x00\x00D\xfe`\xe0\xb9\xaaP\xc0\x00\xa3\xe8\x81\x8f\x012@\xfe'201< 0.1%
 
b'\x00\x01\xad\x10\x00\x00\xa8\x8f\x87\xbe\xbbZP\xc0\x90\xb1\xf7\xe2\x8b\x1e2@\xa8\x8f\x87\xbe\xbbZP\xc0\x90\xb1\xf7\xe2\x8b\x1e2@|\x01\x00\x00\x00\xa8\x8f\x87\xbe\xbbZP\xc0\x90\xb1\xf7\xe2\x8b\x1e2@\xfe'192< 0.1%
 
b'\x00\x01\xad\x10\x00\x00X\xd3\xbc\xe3\x14\xc1W\xc0`[\xb1\xbf\xec\xeeG@X\xd3\xbc\xe3\x14\xc1W\xc0`[\xb1\xbf\xec\xeeG@|\x01\x00\x00\x00X\xd3\xbc\xe3\x14\xc1W\xc0`[\xb1\xbf\xec\xeeG@\xfe'184< 0.1%
 
b'\x00\x01\xad\x10\x00\x00\xc4Ia\xde\xe3\x9cP\xc0\x10\xd30|D\x042@\xc4Ia\xde\xe3\x9cP\xc0\x10\xd30|D\x042@|\x01\x00\x00\x00\xc4Ia\xde\xe3\x9cP\xc0\x10\xd30|D\x042@\xfe'180< 0.1%
 
b'\x00\x01\xad\x10\x00\x00ph\x91\xed|\x17X\xc0\xc0\xb8\x8d\x06\xf0\x0eE@ph\x91\xed|\x17X\xc0\xc0\xb8\x8d\x06\xf0\x0eE@|\x01\x00\x00\x00ph\x91\xed|\x17X\xc0\xc0\xb8\x8d\x06\xf0\x0eE@\xfe'176< 0.1%
 
b'\x00\x01\xad\x10\x00\x00\xd0\xe2\x8caN\xbcP\xc0\xd0\x1fE\x9d\xb9\x172@\xd0\xe2\x8caN\xbcP\xc0\xd0\x1fE\x9d\xb9\x172@|\x01\x00\x00\x00\xd0\xe2\x8caN\xbcP\xc0\xd0\x1fE\x9d\xb9\x172@\xfe'175< 0.1%
 
b'\x00\x01\xad\x10\x00\x00\x8c\xf9\x80@g\x85P\xc0\xa0_x%\xc9\xfb1@\x8c\xf9\x80@g\x85P\xc0\xa0_x%\xc9\xfb1@|\x01\x00\x00\x00\x8c\xf9\x80@g\x85P\xc0\xa0_x%\xc9\xfb1@\xfe'170< 0.1%
 
b'\x00\x01\xad\x10\x00\x00(\x87\x16\xd9\xce\xeb^\xc0\x80\x83/L\xa6\x8aD@(\x87\x16\xd9\xce\xeb^\xc0\x80\x83/L\xa6\x8aD@|\x01\x00\x00\x00(\x87\x16\xd9\xce\xeb^\xc0\x80\x83/L\xa6\x8aD@\xfe'164< 0.1%
 
b'\x00\x01\xad\x10\x00\x00\xa4\xc2\x9f\xe1\xcd\x87P\xc0\x80\x8b\xc0X\xdf\xf41@\xa4\xc2\x9f\xe1\xcd\x87P\xc0\x80\x8b\xc0X\xdf\xf41@|\x01\x00\x00\x00\xa4\xc2\x9f\xe1\xcd\x87P\xc0\x80\x8b\xc0X\xdf\xf41@\xfe'164< 0.1%
 
b'\x00\x01\xad\x10\x00\x00L\x15\x8cJ\xea\x9c[\xc0p\x00o\x81\x04\xad@@L\x15\x8cJ\xea\x9c[\xc0p\x00o\x81\x04\xad@@|\x01\x00\x00\x00L\x15\x8cJ\xea\x9c[\xc0p\x00o\x81\x04\xad@@\xfe'164< 0.1%
 
b'\x00\x01\xad\x10\x00\x00\xf4\xc9Q\x80(\xcbP\xc0\x90#\xbag]\x172@\xf4\xc9Q\x80(\xcbP\xc0\x90#\xbag]\x172@|\x01\x00\x00\x00\xf4\xc9Q\x80(\xcbP\xc0\x90#\xbag]\x172@\xfe'164< 0.1%
 
b'\x00\x01\xad\x10\x00\x000\x9b\xc7a0\xc5P\xc0\xe0!\xfeaKg2@0\x9b\xc7a0\xc5P\xc0\xe0!\xfeaKg2@|\x01\x00\x00\x000\x9b\xc7a0\xc5P\xc0\xe0!\xfeaKg2@\xfe'158< 0.1%
 
Other values (1569683)187435599.7%
 
2020-11-18T18:04:41.110826image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1439785 ?
Unique (%)76.6%
2020-11-18T18:04:41.262920image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length216
Median length171
Mean length172.4251486
Min length105

Overview of Unicode Properties

Unique unicode characters95
Unique unicode categories12 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
\7026155821.7%
 
x6857137921.1%
 
04312577113.3%
 
c136098844.2%
 
1122255283.8%
 
f92249212.8%
 
891796252.8%
 
e86582782.7%
 
b84707722.6%
 
a82133152.5%
 
d80687632.5%
 
@71426582.2%
 
966016382.0%
 
'38341051.2%
 
433107581.0%
 
326521740.8%
 
725286730.8%
 
524444450.8%
 
223820870.7%
 
621926550.7%
 
|21412190.7%
 
T12892080.4%
 
A11783730.4%
 
W7807860.2%
 
D7800060.2%
 
Other values (70)253708787.8%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter13041087240.2%
 
Decimal Number8664335426.7%
 
Other Punctuation8440232926.0%
 
Uppercase Letter143020414.4%
 
Math Symbol38758791.2%
 
Open Punctuation12814590.4%
 
Modifier Symbol11774700.4%
 
Close Punctuation9661080.3%
 
Space Separator4451160.1%
 
Currency Symbol2722320.1%
 
Connector Punctuation2705730.1%
 
Dash Punctuation1920240.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
x6857137952.6%
 
c1360988410.4%
 
f92249217.1%
 
e86582786.6%
 
b84707726.5%
 
a82133156.3%
 
d80687636.2%
 
p6496590.5%
 
n5043270.4%
 
t4767480.4%
 
r4260780.3%
 
h3860160.3%
 
z3582780.3%
 
l3187140.2%
 
w2612430.2%
 
i2202570.2%
 
u2182170.2%
 
q2163990.2%
 
s2118750.2%
 
j2060160.2%
 
m2056530.2%
 
o2003190.2%
 
v1938900.1%
 
g1881270.1%
 
y1838340.1%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
\7026155883.2%
 
@71426588.5%
 
'38341054.5%
 
?6160980.7%
 
"3737020.4%
 
,2858490.3%
 
:2598240.3%
 
/2273610.3%
 
;2193120.3%
 
&2106270.2%
 
!2093280.2%
 
%2027880.2%
 
#1979730.2%
 
.1817130.2%
 
*1794330.2%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
04312577149.8%
 
11222552814.1%
 
8917962510.6%
 
966016387.6%
 
433107583.8%
 
326521743.1%
 
725286732.9%
 
524444452.8%
 
223820872.7%
 
621926552.5%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_270573100.0%
 

Most frequent Modifier Symbol characters

ValueCountFrequency (%) 
^70673160.0%
 
`47073940.0%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
T12892089.0%
 
A11783738.2%
 
W7807865.5%
 
D7800065.5%
 
X7741025.4%
 
U7654955.4%
 
B7626455.3%
 
V6773284.7%
 
C6339154.4%
 
G6164314.3%
 
P6078274.2%
 
S6039514.2%
 
F5837914.1%
 
E5659174.0%
 
H5468103.8%
 
R5043783.5%
 
Z4007192.8%
 
Q3878192.7%
 
Y3490052.4%
 
L2574601.8%
 
N2424001.7%
 
J2122681.5%
 
O2047711.4%
 
M2026141.4%
 
K1996321.4%
 

Most frequent Math Symbol characters

ValueCountFrequency (%) 
|214121955.2%
 
>51655513.3%
 
=44334611.4%
 
<3456158.9%
 
~2322666.0%
 
+1968785.1%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
]56143858.1%
 
}20443521.2%
 
)20023520.7%
 

Most frequent Currency Symbol characters

ValueCountFrequency (%) 
$272232100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(56588444.2%
 
[52428940.9%
 
{19128614.9%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
445116100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-192024100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common17952654455.4%
 
Latin14471291344.6%
 

Most frequent Latin characters

ValueCountFrequency (%) 
x6857137947.4%
 
c136098849.4%
 
f92249216.4%
 
e86582786.0%
 
b84707725.9%
 
a82133155.7%
 
d80687635.6%
 
T12892080.9%
 
A11783730.8%
 
W7807860.5%
 
D7800060.5%
 
X7741020.5%
 
U7654950.5%
 
B7626450.5%
 
V6773280.5%
 
p6496590.4%
 
C6339150.4%
 
G6164310.4%
 
P6078270.4%
 
S6039510.4%
 
F5837910.4%
 
E5659170.4%
 
H5468100.4%
 
R5043780.3%
 
n5043270.3%
 
Other values (27)70706524.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
\7026155839.1%
 
04312577124.0%
 
1122255286.8%
 
891796255.1%
 
@71426584.0%
 
966016383.7%
 
'38341052.1%
 
433107581.8%
 
326521741.5%
 
725286731.4%
 
524444451.4%
 
223820871.3%
 
621926551.2%
 
|21412191.2%
 
^7067310.4%
 
?6160980.3%
 
(5658840.3%
 
]5614380.3%
 
[5242890.3%
 
>5165550.3%
 
`4707390.3%
 
4451160.2%
 
=4433460.2%
 
"3737020.2%
 
<3456150.2%
 
Other values (18)39341372.2%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII324239457100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
\7026155821.7%
 
x6857137921.1%
 
04312577113.3%
 
c136098844.2%
 
1122255283.8%
 
f92249212.8%
 
891796252.8%
 
e86582782.7%
 
b84707722.6%
 
a82133152.5%
 
d80687632.5%
 
@71426582.2%
 
966016382.0%
 
'38341051.2%
 
433107581.0%
 
326521740.8%
 
725286730.8%
 
524444450.8%
 
223820870.7%
 
621926550.7%
 
|21412190.7%
 
T12892080.4%
 
A11783730.4%
 
W7807860.2%
 
D7800060.2%
 
Other values (70)253708787.8%
 

Interactions

2020-11-18T18:01:43.244607image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:43.722599image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:44.178572image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:44.676573image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:45.192569image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:45.733573image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:46.250569image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:46.925604image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:47.372685image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:47.809685image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:48.283721image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:48.771686image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:49.258686image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:49.772352image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:50.266807image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:50.737772image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:51.245773image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:51.728773image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:52.200773image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:52.662807image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:53.094771image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:53.595812image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:54.028776image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:54.496776image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:54.952807image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:55.379812image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:55.792800image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:56.229774image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:56.691775image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:57.132775image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:57.595774image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:58.066772image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:58.526774image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:59.018774image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:59.507733image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:01:59.973125image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:00.420123image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:00.926123image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:01.369158image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:01.832152image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:02.293123image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:02.755780image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:03.172766image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:03.677768image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:04.160768image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:04.716769image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:05.268920image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:05.754362image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:06.233648image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:06.747648image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:07.264657image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:07.736647image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:08.267648image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:08.775648image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:09.260647image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:09.739647image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:10.180651image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:10.633646image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:11.103674image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:11.549687image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:11.992646image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:12.440649image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:12.875682image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:13.338652image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:13.813683image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:14.259688image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:14.696682image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:15.177647image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:15.630648image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:16.093126image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:16.543220image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:16.978355image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:17.421811image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:17.879816image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:18.414000image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:18.828015image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:19.262087image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:19.693084image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:20.124119image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:20.567115image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:21.096086image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:21.562085image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:21.992084image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:22.430152image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:22.872148image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:23.312881image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:23.764880image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:24.204233image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:24.662133image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:25.172124image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:25.643123image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:26.134124image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:26.608126image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:27.091122image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:27.542122image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:27.995136image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:28.438127image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:28.845478image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:29.288698image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:29.741789image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:30.228796image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:30.660824image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:31.091789image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:31.544792image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:31.987829image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:32.456824image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:32.900790image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:33.372824image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:33.804789image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:34.234476image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:34.674474image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:35.146478image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:35.621478image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:36.086519image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:36.544475image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:37.004509image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:37.460475image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:37.910474image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:38.371475image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:38.833510image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:39.421506image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:39.894474image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:40.356479image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:40.858474image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:41.358474image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:41.844475image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:42.333477image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:42.813509image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:43.277475image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:43.761474image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:44.222474image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:44.702478image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:45.192474image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:45.651476image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:46.157504image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:46.650513image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:47.112854image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:47.552882image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:47.984853image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:48.460583image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:48.941949image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:49.432152image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:49.919117image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:02:50.390117image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Correlations

2020-11-18T18:04:41.391952image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-11-18T18:04:41.593504image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-11-18T18:04:41.788533image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-11-18T18:04:42.001502image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2020-11-18T18:04:42.266570image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2020-11-18T18:03:10.906128image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:03:20.276614image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:03:38.007964image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-11-18T18:03:44.006574image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Sample

First rows

OBJECTIDFOD_IDFPA_IDSOURCE_SYSTEM_TYPESOURCE_SYSTEMNWCG_REPORTING_AGENCYNWCG_REPORTING_UNIT_IDNWCG_REPORTING_UNIT_NAMESOURCE_REPORTING_UNITSOURCE_REPORTING_UNIT_NAMELOCAL_FIRE_REPORT_IDLOCAL_INCIDENT_IDFIRE_CODEFIRE_NAMEICS_209_INCIDENT_NUMBERICS_209_NAMEMTBS_IDMTBS_FIRE_NAMECOMPLEX_NAMEFIRE_YEARDISCOVERY_DATEDISCOVERY_DOYDISCOVERY_TIMESTAT_CAUSE_CODESTAT_CAUSE_DESCRCONT_DATECONT_DOYCONT_TIMEFIRE_SIZEFIRE_SIZE_CLASSLATITUDELONGITUDEOWNER_CODEOWNER_DESCRSTATECOUNTYFIPS_CODEFIPS_NAMEShape
011FS-1418826FEDFS-FIRESTATFSUSCAPNFPlumas National Forest0511Plumas National Forest1PNF-47BJ8KFOUNTAINNoneNoneNoneNoneNone20052453403.53313009.0Miscellaneous2453403.533.017300.10A40.036944-121.0058335.0USFSCA63063Plumasb'\x00\x01\xad\x10\x00\x00\xe8d\xc2\x92_@^\xc0\xe0\xc8l\x98\xba\x04D@\xe8d\xc2\x92_@^\xc0\xe0\xc8l\x98\xba\x04D@|\x01\x00\x00\x00\xe8d\xc2\x92_@^\xc0\xe0\xc8l\x98\xba\x04D@\xfe'
122FS-1418827FEDFS-FIRESTATFSUSCAENFEldorado National Forest0503Eldorado National Forest1313AAC0PIGEONNoneNoneNoneNoneNone20042453137.513308451.0Lightning2453137.5133.015300.25A38.933056-120.4044445.0USFSCA61061Placerb'\x00\x01\xad\x10\x00\x00T\xb6\xeej\xe2\x19^\xc0\x90\xc6U]nwC@T\xb6\xeej\xe2\x19^\xc0\x90\xc6U]nwC@|\x01\x00\x00\x00T\xb6\xeej\xe2\x19^\xc0\x90\xc6U]nwC@\xfe'
233FS-1418835FEDFS-FIRESTATFSUSCAENFEldorado National Forest0503Eldorado National Forest27021A32WSLACKNoneNoneNoneNoneNone20042453156.515219215.0Debris Burning2453156.5152.020240.10A38.984167-120.73555613.0STATE OR PRIVATECA17017El Doradob'\x00\x01\xad\x10\x00\x00\xd0\xa5\xa0W\x13/^\xc0P\xbbf,\xf9}C@\xd0\xa5\xa0W\x13/^\xc0P\xbbf,\xf9}C@|\x01\x00\x00\x00\xd0\xa5\xa0W\x13/^\xc0P\xbbf,\xf9}C@\xfe'
344FS-1418845FEDFS-FIRESTATFSUSCAENFEldorado National Forest0503Eldorado National Forest436NoneDEERNoneNoneNoneNoneNone20042453184.518016001.0Lightning2453189.5185.014000.10A38.559167-119.9133335.0USFSCA3003Alpineb'\x00\x01\xad\x10\x00\x00\x94\xac\xa3\rt\xfa]\xc0\xe8T\x00\xc6\x92GC@\x94\xac\xa3\rt\xfa]\xc0\xe8T\x00\xc6\x92GC@|\x01\x00\x00\x00\x94\xac\xa3\rt\xfa]\xc0\xe8T\x00\xc6\x92GC@\xfe'
455FS-1418847FEDFS-FIRESTATFSUSCAENFEldorado National Forest0503Eldorado National Forest447NoneSTEVENOTNoneNoneNoneNoneNone20042453184.518016001.0Lightning2453189.5185.012000.10A38.559167-119.9330565.0USFSCA3003Alpineb'\x00\x01\xad\x10\x00\x00@\xe3\xaa.\xb7\xfb]\xc0\xe8T\x00\xc6\x92GC@@\xe3\xaa.\xb7\xfb]\xc0\xe8T\x00\xc6\x92GC@|\x01\x00\x00\x00@\xe3\xaa.\xb7\xfb]\xc0\xe8T\x00\xc6\x92GC@\xfe'
566FS-1418849FEDFS-FIRESTATFSUSCAENFEldorado National Forest0503Eldorado National Forest548NoneHIDDENNoneNoneNoneNoneNone20042453186.518218001.0Lightning2453187.5183.016000.10A38.635278-120.1036115.0USFSCA5005Amadorb'\x00\x01\xad\x10\x00\x00\xf0<~\x90\xa1\x06^\xc0\xe0|D\xc8PQC@\xf0<~\x90\xa1\x06^\xc0\xe0|D\xc8PQC@|\x01\x00\x00\x00\xf0<~\x90\xa1\x06^\xc0\xe0|D\xc8PQC@\xfe'
677FS-1418851FEDFS-FIRESTATFSUSCAENFEldorado National Forest0503Eldorado National Forest589NoneFORKNoneNoneNoneNoneNone20042453187.518318001.0Lightning2453188.5184.014000.10A38.688333-120.1533335.0USFSCA17017El Doradob'\x00\x01\xad\x10\x00\x00$o\x996\xd0\t^\xc0h\x8czN\x1bXC@$o\x996\xd0\t^\xc0h\x8czN\x1bXC@|\x01\x00\x00\x00$o\x996\xd0\t^\xc0h\x8czN\x1bXC@\xfe'
788FS-1418854FEDFS-FIRESTATFSUSCASHFShasta-Trinity National Forest0514Shasta-Trinity National Forest302BK5XSLATENoneNoneNoneNoneNone20052453437.56713005.0Debris Burning2453437.567.016000.80B40.968056-122.43388913.0STATE OR PRIVATECANoneNoneNoneb'\x00\x01\xad\x10\x00\x00t)\xe8\xd5\xc4\x9b^\xc0\xa0t\x9d>\xe9{D@t)\xe8\xd5\xc4\x9b^\xc0\xa0t\x9d>\xe9{D@|\x01\x00\x00\x00t)\xe8\xd5\xc4\x9b^\xc0\xa0t\x9d>\xe9{D@\xfe'
899FS-1418856FEDFS-FIRESTATFSUSCASHFShasta-Trinity National Forest0514Shasta-Trinity National Forest503BLPQSHASTANoneNoneNoneNoneNone20052453444.57412005.0Debris Burning2453444.574.017001.00B41.233611-122.28333313.0STATE OR PRIVATECANoneNoneNoneb'\x00\x01\xad\x10\x00\x00\xdc\x8d\x1e""\x92^\xc0X\xb7\x06\xf8\xe6\x9dD@\xdc\x8d\x1e""\x92^\xc0X\xb7\x06\xf8\xe6\x9dD@|\x01\x00\x00\x00\xdc\x8d\x1e""\x92^\xc0X\xb7\x06\xf8\xe6\x9dD@\xfe'
91010FS-1418859FEDFS-FIRESTATFSUSCAENFEldorado National Forest0503Eldorado National Forest6110NoneTANGLEFOOTNoneNoneNoneNoneNone20042453187.518318001.0Lightning2453188.5184.018000.10A38.548333-120.1491675.0USFSCA5005Amadorb'\x00\x01\xad\x10\x00\x00dS\\\xf2\x8b\t^\xc0\x18\xd4[\xc9/FC@dS\\\xf2\x8b\t^\xc0\x18\xd4[\xc9/FC@|\x01\x00\x00\x00dS\\\xf2\x8b\t^\xc0\x18\xd4[\xc9/FC@\xfe'

Last rows

OBJECTIDFOD_IDFPA_IDSOURCE_SYSTEM_TYPESOURCE_SYSTEMNWCG_REPORTING_AGENCYNWCG_REPORTING_UNIT_IDNWCG_REPORTING_UNIT_NAMESOURCE_REPORTING_UNITSOURCE_REPORTING_UNIT_NAMELOCAL_FIRE_REPORT_IDLOCAL_INCIDENT_IDFIRE_CODEFIRE_NAMEICS_209_INCIDENT_NUMBERICS_209_NAMEMTBS_IDMTBS_FIRE_NAMECOMPLEX_NAMEFIRE_YEARDISCOVERY_DATEDISCOVERY_DOYDISCOVERY_TIMESTAT_CAUSE_CODESTAT_CAUSE_DESCRCONT_DATECONT_DOYCONT_TIMEFIRE_SIZEFIRE_SIZE_CLASSLATITUDELONGITUDEOWNER_CODEOWNER_DESCRSTATECOUNTYFIPS_CODEFIPS_NAMEShape
188045518804563003483112015CAIRS27458827NONFEDST-CACDFST/C&LUSCATCUTuolumne-Calaveras UnitCATCUTuolumne-Calaveras Unit592668006603NoneCOVENoneNoneNoneNoneNone20152457201.517920429.0Miscellaneous2457202.5180.000005.30B37.936253-120.61374313.0STATE OR PRIVATECANoneNoneNoneb"\x00\x01\xad\x10\x00\x00\x84I\xb8\x90G'^\xc0 \xe4g#\xd7\xf7B@\x84I\xb8\x90G'^\xc0 \xe4g#\xd7\xf7B@|\x01\x00\x00\x00\x84I\xb8\x90G'^\xc0 \xe4g#\xd7\xf7B@\xfe"
188045618804573003483282015CAIRS27369138NONFEDST-CACDFST/C&LUSCATGUTehama-Glenn UnitCATGUTehama-Glenn Unit580277005039NoneRANCHO 6NoneNoneNoneNoneNone20152457187.5165171413.0Missing/Undefined2457187.5165.019132.22B40.019907-122.39139813.0STATE OR PRIVATECANoneNoneNoneb'\x00\x01\xad\x10\x00\x00\x10n2\xaa\x0c\x99^\xc0\x18\xfb\x04P\x8c\x02D@\x10n2\xaa\x0c\x99^\xc0\x18\xfb\x04P\x8c\x02D@|\x01\x00\x00\x00\x10n2\xaa\x0c\x99^\xc0\x18\xfb\x04P\x8c\x02D@\xfe'
188045718804583003483542015CAIRS28234594NONFEDST-CACDFST/C&LUSCASHUShasta-Trinity UnitCASHUShasta-Trinity Unit591111009503NoneCARRNoneNoneNoneNoneNone20152457295.527323577.0Arson2457296.5274.000561.00B40.588583-123.06961713.0STATE OR PRIVATECANoneNoneNoneb'\x00\x01\xad\x10\x00\x00\xb8\x8f\xdc\x9at\xc4^\xc0\xa8\xfd\x0f\xb0VKD@\xb8\x8f\xdc\x9at\xc4^\xc0\xa8\xfd\x0f\xb0VKD@|\x01\x00\x00\x00\xb8\x8f\xdc\x9at\xc4^\xc0\xa8\xfd\x0f\xb0VKD@\xfe'
188045818804593003483612015CAIRS27957490NONFEDST-CACDFST/C&LUSCAHUUHumboldt-Del Norte UnitCAHUUHumboldt-Del Norte Unit599566005748None1-64NoneNoneNoneNoneNone20152457235.521313311.0Lightning2457240.5218.010004.00B40.244833-123.54416715.0UNDEFINED FEDERALCANoneNoneNoneb'\x00\x01\xad\x10\x00\x00\xfc#\xd3\xa1\xd3\xe2^\xc0\xa8\xfd\x0f\xb0V\x1fD@\xfc#\xd3\xa1\xd3\xe2^\xc0\xa8\xfd\x0f\xb0V\x1fD@|\x01\x00\x00\x00\xfc#\xd3\xa1\xd3\xe2^\xc0\xa8\xfd\x0f\xb0V\x1fD@\xfe'
188045918804603003483622015CAIRS28291374NONFEDST-CACDFST/C&LUSCALNUSonoma-Lake Napa UnitCALNUSonoma-Lake Napa Unit590768004397NoneBENNETTNoneNoneNoneNoneNone20152457170.514814209.0Miscellaneous2457170.5148.014360.50B38.415608-122.66004413.0STATE OR PRIVATECANoneNoneNoneb'\x00\x01\xad\x10\x00\x00\xf0z0)>\xaa^\xc0h\xfa\x97\xa425C@\xf0z0)>\xaa^\xc0h\xfa\x97\xa425C@|\x01\x00\x00\x00\xf0z0)>\xaa^\xc0h\xfa\x97\xa425C@\xfe'
188046018804613003483632015CAIRS29019636NONFEDST-CACDFST/C&LUSCASHUShasta-Trinity UnitCASHUShasta-Trinity Unit591814009371NoneODESSA 2NoneNoneNoneNoneNone20152457291.5269172613.0Missing/Undefined2457291.5269.018430.01A40.481637-122.38937513.0STATE OR PRIVATECANoneNoneNoneb'\x00\x01\xad\x10\x00\x00P\xb8\x1e\x85\xeb\x98^\xc0\x98\xc5\xfdG\xa6=D@P\xb8\x1e\x85\xeb\x98^\xc0\x98\xc5\xfdG\xa6=D@|\x01\x00\x00\x00P\xb8\x1e\x85\xeb\x98^\xc0\x98\xc5\xfdG\xa6=D@\xfe'
188046118804623003483732015CAIRS29217935NONFEDST-CACDFST/C&LUSCATCUTuolumne-Calaveras UnitCATCUTuolumne-Calaveras Unit569419000366NoneNoneNoneNoneNoneNoneNone20152457300.527801269.0MiscellaneousNaNNaNNone0.20A37.617619-120.93857012.0MUNICIPAL/LOCALCANoneNoneNoneb'\x00\x01\xad\x10\x00\x00\x00\x80\xbe\x88\x11<^\xc0\xa8\xca\x06%\x0e\xcfB@\x00\x80\xbe\x88\x11<^\xc0\xa8\xca\x06%\x0e\xcfB@|\x01\x00\x00\x00\x00\x80\xbe\x88\x11<^\xc0\xa8\xca\x06%\x0e\xcfB@\xfe'
188046218804633003483752015CAIRS28364460NONFEDST-CACDFST/C&LUSCATCUTuolumne-Calaveras UnitCATCUTuolumne-Calaveras Unit574245000158NoneNoneNoneNoneNoneNoneNone20152457144.5122205213.0Missing/UndefinedNaNNaNNone0.10A37.617619-120.93857012.0MUNICIPAL/LOCALCANoneNoneNoneb'\x00\x01\xad\x10\x00\x00\x00\x80\xbe\x88\x11<^\xc0\xa8\xca\x06%\x0e\xcfB@\x00\x80\xbe\x88\x11<^\xc0\xa8\xca\x06%\x0e\xcfB@|\x01\x00\x00\x00\x00\x80\xbe\x88\x11<^\xc0\xa8\xca\x06%\x0e\xcfB@\xfe'
188046318804643003483772015CAIRS29218079NONFEDST-CACDFST/C&LUSCATCUTuolumne-Calaveras UnitCATCUTuolumne-Calaveras Unit570462000380NoneNoneNoneNoneNoneNoneNone20152457309.5287230913.0Missing/UndefinedNaNNaNNone2.00B37.672235-120.89835612.0MUNICIPAL/LOCALCANoneNoneNoneb'\x00\x01\xad\x10\x00\x00x\xba_\xaa~9^\xc0\xb8dL\xc9\x0b\xd6B@x\xba_\xaa~9^\xc0\xb8dL\xc9\x0b\xd6B@|\x01\x00\x00\x00x\xba_\xaa~9^\xc0\xb8dL\xc9\x0b\xd6B@\xfe'
188046418804653003483992015CAIRS26733926NONFEDST-CACDFST/C&LUSCABDUSan Bernardino UnitCABDUCDF - San Bernardino Unit535436003225NoneBARKER BL BIG_BEAR_LAKE_NoneNoneNoneNoneNone20152457095.57321289.0MiscellaneousNaNNaNNone0.10A34.263217-116.83095013.0STATE OR PRIVATECANoneNoneNoneb'\x00\x01\xad\x10\x00\x00\x1c\xa7\xe8H.5]\xc00`;\x18\xb1!A@\x1c\xa7\xe8H.5]\xc00`;\x18\xb1!A@|\x01\x00\x00\x00\x1c\xa7\xe8H.5]\xc00`;\x18\xb1!A@\xfe'